| 1. |
- de Jong, Roelof S., et al.
(författare)
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4MOST-4-metre Multi-Object Spectroscopic Telescope
- 2014
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Ingår i: Ground-based and Airborne Instrumentation for Astronomy V. - : SPIE. - 0277-786X .- 1996-756X. ; 9147
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Konferensbidrag (refereegranskat)abstract
- 4MOST is a wide-field, high-multiplex spectroscopic survey facility under development for the VISTA telescope of the European Southern Observatory (ESO). Its main science drivers are in the fields of galactic archeology, high-energy physics, galaxy evolution and cosmology. 4MOST will in particular provide the spectroscopic complements to the large area surveys coming from space missions like Gaia, eROSITA, Euclid, and PLATO and from ground-based facilities like VISTA, VST, DES, LSST and SKA. The 4MOST baseline concept features a 2.5 degree diameter field-of-view with similar to 2400 fibres in the focal surface that are configured by a fibre positioner based on the tilting spine principle. The fibres feed two types of spectrographs; similar to 1600 fibres go to two spectrographs with resolution R> 5000 (lambda similar to 390-930 nm) and similar to 800 fibres to a spectrograph with R> 18,000 (lambda similar to 392-437 nm & 515-572 nm & 605-675 nm). Both types of spectrographs are fixed-configuration, three-channel spectrographs. 4MOST will have an unique operations concept in which 5 year public surveys from both the consortium and the ESO community will be combined and observed in parallel during each exposure, resulting in more than 25 million spectra of targets spread over a large fraction of the southern sky. The 4MOST Facility Simulator (4FS) was developed to demonstrate the feasibility of this observing concept. 4MOST has been accepted for implementation by ESO with operations expected to start by the end of 2020. This paper provides a top-level overview of the 4MOST facility, while other papers in these proceedings provide more detailed descriptions of the instrument concept[1], the instrument requirements development[2], the systems engineering implementation[3], the instrument model[4], the fibre positioner concepts[5], the fibre feed[6], and the spectrographs[7].
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| 11. |
- Bender, Andreas, et al.
(författare)
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Evaluation guidelines for machine learning tools in the chemical sciences
- 2022
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Ingår i: Nature Reviews Chemistry. - : Springer Science and Business Media LLC. - 2397-3358. ; 6:6, s. 428-442
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Tidskriftsartikel (refereegranskat)abstract
- Machine learning (ML) promises to tackle the grand challenges in chemistry and speed up the generation, improvement and/or ordering of research hypotheses. Despite the overarching applicability of ML workflows, one usually finds diverse evaluation study designs. The current heterogeneity in evaluation techniques and metrics leads to difficulty in (or the impossibility of) comparing and assessing the relevance of new algorithms. Ultimately, this may delay the digitalization of chemistry at scale and confuse method developers, experimentalists, reviewers and journal editors. In this Perspective, we critically discuss a set of method development and evaluation guidelines for different types of ML-based publications, emphasizing supervised learning. We provide a diverse collection of examples from various authors and disciplines in chemistry. While taking into account varying accessibility across research groups, our recommendations focus on reporting completeness and standardizing comparisons between tools. We aim to further contribute to improved ML transparency and credibility by suggesting a checklist of retro-/prospective tests and dissecting their importance. We envisage that the wide adoption and continuous update of best practices will encourage an informed use of ML on real-world problems related to the chemical sciences. [Figure not available: see fulltext.]
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| 12. |
- Bender, Brian J., et al.
(författare)
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A practical guide to large-scale docking
- 2021
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Ingår i: Nature Protocols. - : Springer Nature. - 1754-2189 .- 1750-2799. ; 16:10, s. 4799-4832
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Tidskriftsartikel (refereegranskat)abstract
- Structure-based docking screens of large compound libraries have become common in early drug and probe discovery. As computer efficiency has improved and compound libraries have grown, the ability to screen hundreds of millions, and even billions, of compounds has become feasible for modest-sized computer clusters. This allows the rapid and cost-effective exploration and categorization of vast chemical space into a subset enriched with potential hits for a given target. To accomplish this goal at speed, approximations are used that result in undersampling of possible configurations and inaccurate predictions of absolute binding energies. Accordingly, it is important to establish controls, as are common in other fields, to enhance the likelihood of success in spite of these challenges. Here we outline best practices and control docking calculations that help evaluate docking parameters for a given target prior to undertaking a large-scale prospective screen, with exemplification in one particular target, the melatonin receptor, where following this procedure led to direct docking hits with activities in the subnanomolar range. Additional controls are suggested to ensure specific activity for experimentally validated hit compounds. These guidelines should be useful regardless of the docking software used. Docking software described in the outlined protocol (DOCK3.7) is made freely available for academic research to explore new hits for a range of targets. Structure-based docking screens of compound libraries are common in early drug and probe discovery. This protocol outlines best practices and control calculations to evaluate docking parameters prior to undertaking a large-scale prospective screen.
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| 13. |
- Blanton, Michael R., et al.
(författare)
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Sloan Digital Sky Survey IV : Mapping the Milky Way, Nearby Galaxies, and the Distant Universe
- 2017
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Ingår i: Astronomical Journal. - : IOP Publishing Ltd. - 0004-6256 .- 1538-3881. ; 154:1
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Tidskriftsartikel (refereegranskat)abstract
- We describe the Sloan Digital Sky Survey IV (SDSS-IV), a project encompassing three major spectroscopic programs. The Apache Point Observatory Galactic Evolution Experiment 2 (APOGEE-2) is observing hundreds of thousands of Milky Way stars at high resolution and. high signal-to-noise ratios in the near-infrared. The Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey is obtaining spatially resolved spectroscopy for thousands of nearby galaxies (median z similar to 0.03). The extended Baryon Oscillation Spectroscopic Survey (eBOSS) is mapping the galaxy, quasar, and neutral gas distributions between z similar to 0.6 and 3.5 to constrain cosmology using baryon acoustic oscillations, redshift space distortions, and the shape of the power spectrum. Within eBOSS, we are conducting two major subprograms: the SPectroscopic IDentification of eROSITA Sources (SPIDERS), investigating X-ray AGNs. and galaxies in X-ray clusters, and the Time Domain Spectroscopic Survey (TDSS), obtaining spectra of variable sources. All programs use the 2.5 m Sloan Foundation Telescope at the. Apache Point Observatory; observations there began in Summer 2014. APOGEE-2 also operates a second near-infrared spectrograph at the 2.5 m du Pont Telescope at Las Campanas Observatory, with observations beginning in early 2017. Observations at both facilities are scheduled to continue through 2020. In keeping with previous SDSS policy, SDSS-IV provides regularly scheduled public data releases; the first one, Data Release 13, was made available in 2016 July.
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| 14. |
- Bonner, Stephen, et al.
(författare)
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A review of biomedical datasets relating to drug discovery: a knowledge graph perspective
- 2022
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Ingår i: Briefings in Bioinformatics. - : Oxford University Press (OUP). - 1467-5463 .- 1477-4054. ; In Press
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Forskningsöversikt (refereegranskat)abstract
- Drug discovery and development is a complex and costly process. Machine learning approaches are being investigated to help improve the effectiveness and speed of multiple stages of the drug discovery pipeline. Of these, those that use Knowledge Graphs (KG) have promise in many tasks, including drug repurposing, drug toxicity prediction and target gene-disease prioritization. In a drug discovery KG, crucial elements including genes, diseases and drugs are represented as entities, while relationships between them indicate an interaction. However, to construct high-quality KGs, suitable data are required. In this review, we detail publicly available sources suitable for use in constructing drug discovery focused KGs. We aim to help guide machine learning and KG practitioners who are interested in applying new techniques to the drug discovery field, but who may be unfamiliar with the relevant data sources. The datasets are selected via strict criteria, categorized according to the primary type of information contained within and are considered based upon what information could be extracted to build a KG. We then present a comparative analysis of existing public drug discovery KGs and an evaluation of selected motivating case studies from the literature. Additionally, we raise numerous and unique challenges and issues associated with the domain and its datasets, while also highlighting key future research directions. We hope this review will motivate KGs use in solving key and emerging questions in the drug discovery domain.
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| 15. |
- Bree, N, et al.
(författare)
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Shape Coexistence in the Neutron-Deficient Even-Even Hg182-188 Isotopes Studied via Coulomb Excitation.
- 2014
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Ingår i: Physical Review Letters. - 1079-7114. ; 112:16
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Tidskriftsartikel (refereegranskat)abstract
- Coulomb-excitation experiments to study electromagnetic properties of radioactive even-even Hg isotopes were performed with 2.85 MeV/nucleon mercury beams from REX-ISOLDE. Magnitudes and relative signs of the reduced E2 matrix elements that couple the ground state and low-lying excited states in Hg182-188 were extracted. Information on the deformation of the ground and the first excited 0+ states was deduced using the quadrupole sum rules approach. Results show that the ground state is slightly deformed and of oblate nature, while a larger deformation for the excited 0+ state was noted in Hg182,184. The results are compared to beyond mean field and interacting-boson based models and interpreted within a two-state mixing model. Partial agreement with the model calculations was obtained. The presence of two different structures in the light even-mass mercury isotopes that coexist at low excitation energy is firmly established.
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| 16. |
- Chantzi, Efthymia
(författare)
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Algorithmic discovery, development and personalized selection of higher-order drug cocktails : A label-free live-cell imaging & secretomics approach
- 2020
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- An upward trend in clinical pharmacology is the use of multiple drugs to combat complex and co-occurring diseases due to better efficacy, decreased toxicity and reduced risk of evolving resistance. Despite high late-stage attrition rates and the need for multi drug treatments, most drug discovery and development efforts are still mainly focused on new one-size-fits-all monotherapies. This is unfortunate given the complex, heterogeneous and often only partially understood pathophysiology of many diseases. In this context, polypharmacotherapies hold strong potential, especially when patient tailored. However, as of today, the personalized combination therapy area remains vastly unexplored. A major reason is lack of standardized and robust tools that allow systematic in vitro drug combination sensitivity testing of different disease models and patient derived cells.This thesis fills in this lack by introducing two methodological frameworks, namely COMBImageDL and COMBSecretomics, designed to enable systematic second- and higher-order drug combination studies within and beyond cancer pharmacology. They include advanced quality control procedures, non-parametric resampling statistics to quantify uncertainty and a data driven methodology to evaluate response patterns and discern higher- from lower- and single-drug effects. Both are based on a standardized and reproducible format that could be employed with any experimental platform that provides the required raw data. COMBImageDL searches exhaustively for drug cocktails that induce changes in cell viability and time evolving cell culture morphology by employing conventional endpoint synergy analyses jointly with quantitative label-free live-cell imaging. Deep neural network learning, MapReduce parallel processing and method-specific parameter tuning are key components of the design. The purely phenotypic functionality of COMBImageDL is extended by COMBSecretomics, which searches exhaustively for drug cocktails that can modify, or even reverse malfunctioning secretomic patterns. It processes complex datasets involving drug treated cells observed before and after being stimulated by relevant proteins. Finally, the highest single agent method is generalized for higher-order drug combination analysis and adjusted for secreted protein profiles.The frameworks were used in five pharmacological studies being industrial, academic and clinical collaborations in areas where novel and personalized multi drug regimens are highly needed; oncology (acute myeloid leukemia and glioblastoma multiforme) and osteoarthritis. These studies demonstrate intriguing drug combination findings and in general the great potential of tools like COMBImageDL and COMBSecretomics to accelerate the discovery and development of novel potent polypharmacotherapeutic candidates.
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| 17. |
- De Jong, R. S., et al.
(författare)
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4MOST - 4-metre multi-object spectroscopic telescope
- 2012
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Ingår i: Proceedings of SPIE - The International Society for Optical Engineering. - : SPIE. - 9780819491473 ; , s. 84460T-
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Konferensbidrag (refereegranskat)abstract
- The 4MOST consortium is currently halfway through a Conceptual Design study for ESO with the aim to develop a wide-field (>3 square degree, goal >5 square degree), high-multiplex (>1500 fibres, goal 3000 fibres) spectroscopic survey facility for an ESO 4m-class telescope (VISTA). 4MOST will run permanently on the telescope to perform a 5 year public survey yielding more than 20 million spectra at resolution R∼5000 (λ=390-1000 nm) and more than 2 million spectra at R∼20,000 (395-456.5 nm & 587-673 nm). The 4MOST design is especially intended to complement three key all-sky, space-based observatories of prime European interest: Gaia, eROSITA and Euclid. Initial design and performance estimates for the wide-field corrector concepts are presented. Two fibre positioner concepts are being considered for 4MOST. The first one is a Phi-Theta system similar to ones used on existing and planned facilities. The second one is a new R-Theta concept with large patrol area. Both positioner concepts effectively address the issues of fibre focus and pupil pointing. The 4MOST spectrographs are fixed configuration two-arm spectrographs, with dedicated spectrographs for the high- and low-resolution fibres. A full facility simulator is being developed to guide trade-off decisions regarding the optimal field-of-view, number of fibres needed, and the relative fraction of high-to-low resolution fibres. The simulator takes mock catalogues with template spectra from Design Reference Surveys as starting point, calculates the output spectra based on a throughput simulator, assigns targets to fibres based on the capabilities of the fibre positioner designs, and calculates the required survey time by tiling the fields on the sky. The 4MOST consortium aims to deliver the full 4MOST facility by the end of 2018 and start delivering high-level data products for both consortium and ESO community targets a year later with yearly increments.
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| 18. |
- Gaffney, L. P., et al.
(författare)
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Collectivity in the light radon nuclei measured directly via Coulomb excitation
- 2015
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Ingår i: Physical Review C (Nuclear Physics). - 0556-2813. ; 91:6
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Tidskriftsartikel (refereegranskat)abstract
- Background: Shape coexistence in heavy nuclei poses a strong challenge to state-of-the-art nuclear models, where several competing shape minima are found close to the ground state. A classic region for investigating this phenomenon is in the region around Z = 82 and the neutron midshell at N = 104. Purpose: Evidence for shape coexistence has been inferred from a-decay measurements, laser spectroscopy, and in-beam measurements. While the latter allow the pattern of excited states and rotational band structures to be mapped out, a detailed understanding of shape coexistence can only come from measurements of electromagnetic matrix elements. Method: Secondary, radioactive ion beams of Rn-202 and Rn-204 were studied by means of low-energy Coulomb excitation at the REX-ISOLDE in CERN. Results: The electric-quadrupole (E2) matrix element connecting the ground state and first excited 2(1)(+) state was extracted for both Rn-202 and Rn-204, corresponding to B(E2; 2(1)(+) -> 0(1)(+)) = 29(-8)(+8) and 43(-12)(+17) W.u., respectively. Additionally, E2 matrix elements connecting the 2(1)(+) state with the 4(1)(+) and 2(2)(+) states were determined in Rn-202. No excited 0(+) states were observed in the current data set, possibly owing to a limited population of second-order processes at the currently available beam energies. Conclusions: The results are discussed in terms of collectivity and the deformation of both nuclei studied is deduced to be weak, as expected from the low-lying level-energy schemes. Comparisons are also made to state-of-the-art beyond-mean-field model calculations and the magnitude of the transitional quadrupole moments are well reproduced.
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| 19. |
- Günther, Felix, et al.
(författare)
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Nowcasting the COVID-19 pandemic in Bavaria
- 2021
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Ingår i: Biometrical Journal. - : Wiley. - 0323-3847 .- 1521-4036. ; 63:3, s. 490-502
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Tidskriftsartikel (refereegranskat)abstract
- To assess the current dynamics of an epidemic, it is central to collect information on the daily number of newly diseased cases. This is especially important in real-time surveillance, where the aim is to gain situational awareness, for example, if cases are currently increasing or decreasing. Reporting delays between disease onset and case reporting hamper our ability to understand the dynamics of an epidemic close to now when looking at the number of daily reported cases only. Nowcasting can be used to adjust daily case counts for occurred-but-not-yet-reported events. Here, we present a novel application of nowcasting to data on the current COVID-19 pandemic in Bavaria. It is based on a hierarchical Bayesian model that considers changes in the reporting delay distribution over time and associated with the weekday of reporting. Furthermore, we present a way to estimate the effective time-varying case reproduction number Re(t) based on predictions of the nowcast. The approaches are based on previously published work, that we considerably extended and adapted to the current task of nowcasting COVID-19 cases. We provide methodological details of the developed approach, illustrate results based on data of the current pandemic, and evaluate the model based on synthetic and retrospective data on COVID-19 in Bavaria. Results of our nowcasting are reported to the Bavarian health authority and published on a webpage on a daily basis (https://corona.stat.uni-muenchen.de/). Code and synthetic data for the analysis are available from https://github.com/FelixGuenther/nc_covid19_bavaria and can be used for adaption of our approach to different data.
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| 20. |
- Küchenhoff, Helmut, et al.
(författare)
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Analysis of the early COVID-19 epidemic curve in Germany by regression models with change points
- 2021
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Ingår i: Epidemiology and Infection. - 0950-2688 .- 1469-4409. ; 149, s. 1-7
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Tidskriftsartikel (refereegranskat)abstract
- We analysed the coronavirus disease 2019 epidemic curve from March to the end of April 2020 in Germany. We use statistical models to estimate the number of cases with disease onset on a given day and use back-projection techniques to obtain the number of new infections per day. The respective time series are analysed by a trend regression model with change points. The change points are estimated directly from the data. We carry out the analysis for the whole of Germany and the federal state of Bavaria, where we have more detailed data. Both analyses show a major change between 9 and 13 March for the time series of infections: from a strong increase to a decrease. Another change was found between 25 March and 29 March, where the decline intensified. Furthermore, we perform an analysis stratified by age. A main result is a delayed course of the pandemic for the age group 80 + resulting in a turning point at the end of March. Our results differ from those by other authors as we take into account the reporting delay, which turned out to be time dependent and therefore changes the structure of the epidemic curve compared to the curve of newly reported cases.
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| 21. |
- Mervin, Lewis H., et al.
(författare)
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Probabilistic Random Forest improves bioactivity predictions close to the classification threshold by taking into account experimental uncertainty
- 2021
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Ingår i: Journal of Cheminformatics. - : Springer Science and Business Media LLC. - 1758-2946 .- 1758-2946. ; 13:1
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Tidskriftsartikel (refereegranskat)abstract
- Measurements of protein–ligand interactions have reproducibility limits due to experimental errors. Any model based on such assays will consequentially have such unavoidable errors influencing their performance which should ideally be factored into modelling and output predictions, such as the actual standard deviation of experimental measurements (σ) or the associated comparability of activity values between the aggregated heterogenous activity units (i.e., Ki versus IC50 values) during dataset assimilation. However, experimental errors are usually a neglected aspect of model generation. In order to improve upon the current state-of-the-art, we herein present a novel approach toward predicting protein–ligand interactions using a Probabilistic Random Forest (PRF) classifier. The PRF algorithm was applied toward in silico protein target prediction across ~ 550 tasks from ChEMBL and PubChem. Predictions were evaluated by taking into account various scenarios of experimental standard deviations in both training and test sets and performance was assessed using fivefold stratified shuffled splits for validation. The largest benefit in incorporating the experimental deviation in PRF was observed for data points close to the binary threshold boundary, when such information was not considered in any way in the original RF algorithm. For example, in cases when σ ranged between 0.4–0.6 log units and when ideal probability estimates between 0.4–0.6, the PRF outperformed RF with a median absolute error margin of ~ 17%. In comparison, the baseline RF outperformed PRF for cases with high confidence to belong to the active class (far from the binary decision threshold), although the RF models gave errors smaller than the experimental uncertainty, which could indicate that they were overtrained and/or over-confident. Finally, the PRF models trained with putative inactives decreased the performance compared to PRF models without putative inactives and this could be because putative inactives were not assigned an experimental pXC50 value, and therefore they were considered inactives with a low uncertainty (which in practice might not be true). In conclusion, PRF can be useful for target prediction models in particular for data where class boundaries overlap with the measurement uncertainty, and where a substantial part of the training data is located close to the classification threshold.
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| 22. |
- Nowak-Sliwinska, Patrycja, et al.
(författare)
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Consensus guidelines for the use and interpretation of angiogenesis assays
- 2018
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Ingår i: Angiogenesis. - : Springer. - 0969-6970 .- 1573-7209. ; 21:3, s. 425-532
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Forskningsöversikt (refereegranskat)abstract
- The formation of new blood vessels, or angiogenesis, is a complex process that plays important roles in growth and development, tissue and organ regeneration, as well as numerous pathological conditions. Angiogenesis undergoes multiple discrete steps that can be individually evaluated and quantified by a large number of bioassays. These independent assessments hold advantages but also have limitations. This article describes in vivo, ex vivo, and in vitro bioassays that are available for the evaluation of angiogenesis and highlights critical aspects that are relevant for their execution and proper interpretation. As such, this collaborative work is the first edition of consensus guidelines on angiogenesis bioassays to serve for current and future reference.
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| 23. |
- Poli, Sven, et al.
(författare)
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Penumbral Rescue by normobaric O?=?O administration in patients with ischemic stroke and target mismatch proFile (PROOF): Study protocol of a phase IIb trial
- 2024
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Ingår i: INTERNATIONAL JOURNAL OF STROKE. - 1747-4930 .- 1747-4949. ; 19:1, s. 120-126
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Tidskriftsartikel (refereegranskat)abstract
- Rationale: Oxygen is essential for cellular energy metabolism. Neurons are particularly vulnerable to hypoxia. Increasing oxygen supply shortly after stroke onset could preserve the ischemic penumbra until revascularization occurs.Aims: PROOF investigates the use of normobaric oxygen (NBO) therapy within 6 h of symptom onset/notice for brain-protective bridging until endovascular revascularization of acute intracranial anterior-circulation occlusion.Methods and design: Randomized (1:1), standard treatment-controlled, open-label, blinded endpoint, multicenter adaptive phase IIb trial.Study outcomes: Primary outcome is ischemic core growth (mL) from baseline to 24 h (intention-to-treat analysis). Secondary efficacy outcomes include change in NIHSS from baseline to 24 h, mRS at 90 days, cognitive and emotional function, and quality of life. Safety outcomes include mortality, intracranial hemorrhage, and respiratory failure. Exploratory analyses of imaging and blood biomarkers will be conducted.Sample size: Using an adaptive design with interim analysis at 80 patients per arm, up to 456 participants (228 per arm) would be needed for 80% power (one-sided alpha 0.05) to detect a mean reduction of ischemic core growth by 6.68 mL, assuming 21.4 mL standard deviation.Discussion: By enrolling endovascular thrombectomy candidates in an early time window, the trial replicates insights from preclinical studies in which NBO showed beneficial effects, namely early initiation of near 100% inspired oxygen during short temporary ischemia. Primary outcome assessment at 24 h on follow-up imaging reduces variability due to withdrawal of care and early clinical confounders such as delayed extubation and aspiration pneumonia.
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| 24. |
- Rodriguez, D., et al.
(författare)
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MATS and LaSpec : High-precision experiments using ion traps and lasers at FAIR
- 2010
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Ingår i: The European physical journal. Special topics. - : Springer Science and Business Media LLC. - 1951-6355 .- 1951-6401. ; 183, s. 1-123
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Forskningsöversikt (refereegranskat)abstract
- Nuclear ground state properties including mass, charge radii, spins and moments can be determined by applying atomic physics techniques such as Penning-trap based mass spectrometry and laser spectroscopy. The MATS and LaSpec setups at the low-energy beamline at FAIR will allow us to extend the knowledge of these properties further into the region far from stability. The mass and its inherent connection with the nuclear binding energy is a fundamental property of a nuclide, a unique ""fingerprint"". Thus, precise mass values are important for a variety of applications, ranging from nuclear-structure studies like the investigation of shell closures and the onset of deformation, tests of nuclear mass models and mass formulas, to tests of the weak interaction and of the Standard Model. The required relative accuracy ranges from 10(-5) to below 10(-8) for radionuclides, which most often have half-lives well below 1 s. Substantial progress in Penning trap mass spectrometry has made this method a prime choice for precision measurements on rare isotopes. The technique has the potential to provide high accuracy and sensitivity even for very short-lived nuclides. Furthermore, ion traps can be used for precision decay studies and offer advantages over existing methods. With MATS (Precision Measurements of very short-lived nuclei using an Advanced Trapping System for highly-charged ions) at FAIR we aim to apply several techniques to very short-lived radionuclides: High-accuracy mass measurements, in-trap conversion electron and alpha spectroscopy, and trap-assisted spectroscopy. The experimental setup of MATS is a unique combination of an electron beam ion trap for charge breeding, ion traps for beam preparation, and a high-precision Penning trap system for mass measurements and decay studies. For the mass measurements, MATS offers both a high accuracy and a high sensitivity. A relative mass uncertainty of 10(-9) can be reached by employing highly-charged ions and a non-destructive Fourier-Transform Ion-Cyclotron-Resonance (FT-ICR) detection technique on single stored ions. This accuracy limit is important for fundamental interaction tests, but also allows for the study of the fine structure of the nuclear mass surface with unprecedented accuracy, whenever required. The use of the FT-ICR technique provides true single ion sensitivity. This is essential to access isotopes that are produced with minimum rates which are very often the most interesting ones. Instead of pushing for highest accuracy, the high charge state of the ions can also be used to reduce the storage time of the ions, hence making measurements on even shorter-lived isotopes possible. Decay studies in ion traps will become possible with MATS. Novel spectroscopic tools for in-trap high-resolution conversion-electron and charged-particle spectroscopy from carrier-free sources will be developed, aiming e. g. at the measurements of quadrupole moments and E0 strengths. With the possibility of both high-accuracy mass measurements of the shortest-lived isotopes and decay studies, the high sensitivity and accuracy potential of MATS is ideally suited for the study of very exotic nuclides that will only be produced at the FAIR facility. Laser spectroscopy of radioactive isotopes and isomers is an efficient and model-independent approach for the determination of nuclear ground and isomeric state properties. Hyperfine structures and isotope shifts in electronic transitions exhibit readily accessible information on the nuclear spin, magnetic dipole and electric quadrupole moments as well as root-mean-square charge radii. The dependencies of the hyperfine splitting and isotope shift on the nuclear moments and mean square nuclear charge radii are well known and the theoretical framework for the extraction of nuclear parameters is well established. These extracted parameters provide fundamental information on the structure of nuclei at the limits of stability. Vital information on both bulk and valence nuclear properties are derived and an exceptional sensitivity to changes in nuclear deformation is achieved. Laser spectroscopy provides the only mechanism for such studies in exotic systems and uniquely facilitates these studies in a model-independent manner. The accuracy of laser-spectroscopic-determined nuclear properties is very high. Requirements concerning production rates are moderate; collinear spectroscopy has been performed with production rates as few as 100 ions per second and laser-desorption resonance ionization mass spectroscopy (combined with beta-delayed neutron detection) has been achieved with rates of only a few atoms per second. This Technical Design Report describes a new Penning trap mass spectrometry setup as well as a number of complementary experimental devices for laser spectroscopy, which will provide a complete system with respect to the physics and isotopes that can be studied. Since MATS and LaSpec require high-quality low-energy beams, the two collaborations have a common beamline to stop the radioactive beam of in-flight produced isotopes and prepare them in a suitable way for transfer to the MATS and LaSpec setups, respectively.
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| 25. |
- Seal, Srijit, et al.
(författare)
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From pixels to phenotypes : Integrating image-based profiling with cell health data as BioMorph features improves interpretability
- 2024
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Ingår i: Molecular Biology of the Cell. - : American Society for Cell Biology (ASCB). - 1059-1524 .- 1939-4586. ; 35:3
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Tidskriftsartikel (refereegranskat)abstract
- Cell Painting assays generate morphological profiles that are versatile descriptors of biological systems and have been used to predict in vitro and in vivo drug effects. However, Cell Painting features extracted from classical software such as CellProfiler are based on statistical calculations and often not readily biologically interpretable. In this study, we propose a new feature space, which we call BioMorph, that maps these Cell Painting features with readouts from comprehensive Cell Health assays. We validated that the resulting BioMorph space effectively connected compounds not only with the morphological features associated with their bioactivity but with deeper insights into phenotypic characteristics and cellular processes associated with the given bioactivity. The BioMorph space revealed the mechanism of action for individual compounds, including dual-acting compounds such as emetine, an inhibitor of both protein synthesis and DNA replication. Overall, BioMorph space offers a biologically relevant way to interpret the cell morphological features derived using software such as CellProfiler and to generate hypotheses for experimental validation.
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| 26. |
- Seal, Srijit, et al.
(författare)
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Insights into Drug Cardiotoxicity from Biological and Chemical Data : The First Public Classifiers for FDA Drug-Induced Cardiotoxicity Rank
- 2024
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Ingår i: Journal of Chemical Information and Modeling. - : American Chemical Society (ACS). - 1549-9596 .- 1549-960X. ; 64:4, s. 1172-1186
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Tidskriftsartikel (refereegranskat)abstract
- Drug-induced cardiotoxicity (DICT) is a major concern in drug development, accounting for 10-14% of postmarket withdrawals. In this study, we explored the capabilities of chemical and biological data to predict cardiotoxicity, using the recently released DICTrank data set from the United States FDA. We found that such data, including protein targets, especially those related to ion channels (e.g., hERG), physicochemical properties (e.g., electrotopological state), and peak concentration in plasma offer strong predictive ability for DICT. Compounds annotated with mechanisms of action such as cyclooxygenase inhibition could distinguish between most-concern and no-concern DICT. Cell Painting features for ER stress discerned most-concern cardiotoxic from nontoxic compounds. Models based on physicochemical properties provided substantial predictive accuracy (AUCPR = 0.93). With the availability of omics data in the future, using biological data promises enhanced predictability and deeper mechanistic insights, paving the way for safer drug development.
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| 27. |
- Seal, Srijit, et al.
(författare)
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Integrating cell morphology with gene expression and chemical structure to aid mitochondrial toxicity detection
- 2022
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Ingår i: Communications Biology. - : Springer Nature. - 2399-3642. ; 5
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Tidskriftsartikel (refereegranskat)abstract
- Cell Painting, gene expression, and chemical structural data are used to examine the differences between mitochondrial toxicants and non-toxicants and enhance the detection of mitotoxic compounds for future drug discovery. Mitochondrial toxicity is an important safety endpoint in drug discovery. Models based solely on chemical structure for predicting mitochondrial toxicity are currently limited in accuracy and applicability domain to the chemical space of the training compounds. In this work, we aimed to utilize both -omics and chemical data to push beyond the state-of-the-art. We combined Cell Painting and Gene Expression data with chemical structural information from Morgan fingerprints for 382 chemical perturbants tested in the Tox21 mitochondrial membrane depolarization assay. We observed that mitochondrial toxicants differ from non-toxic compounds in morphological space and identified compound clusters having similar mechanisms of mitochondrial toxicity, thereby indicating that morphological space provides biological insights related to mechanisms of action of this endpoint. We further showed that models combining Cell Painting, Gene Expression features and Morgan fingerprints improved model performance on an external test set of 244 compounds by 60% (in terms of F1 score) and improved extrapolation to new chemical space. The performance of our combined models was comparable with dedicated in vitro assays for mitochondrial toxicity. Our results suggest that combining chemical descriptors with biological readouts enhances the detection of mitochondrial toxicants, with practical implications in drug discovery.
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| 28. |
- Seal, Srijit, et al.
(författare)
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Merging bioactivity predictions from cell morphology and chemical fingerprint models using similarity to training data
- 2023
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Ingår i: Journal of Cheminformatics. - : BMC. - 1758-2946. ; 15:1
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Tidskriftsartikel (refereegranskat)abstract
- The applicability domain of machine learning models trained on structural fingerprints for the prediction of biological endpoints is often limited by the lack of diversity of chemical space of the training data. In this work, we developed similarity-based merger models which combined the outputs of individual models trained on cell morphology (based on Cell Painting) and chemical structure (based on chemical fingerprints) and the structural and morphological similarities of the compounds in the test dataset to compounds in the training dataset. We applied these similarity-based merger models using logistic regression models on the predictions and similarities as features and predicted assay hit calls of 177 assays from ChEMBL, PubChem and the Broad Institute (where the required Cell Painting annotations were available). We found that the similarity-based merger models outperformed other models with an additional 20% assays (79 out of 177 assays) with an AUC > 0.70 compared with 65 out of 177 assays using structural models and 50 out of 177 assays using Cell Painting models. Our results demonstrated that similarity-based merger models combining structure and cell morphology models can more accurately predict a wide range of biological assay outcomes and further expanded the applicability domain by better extrapolating to new structural and morphology spaces.
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| 29. |
- Svensson, Fredrik, et al.
(författare)
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Conformal Regression for Quantitative Structure-Activity Relationship Modeling-Quantifying Prediction Uncertainty
- 2018
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Ingår i: Journal of Chemical Information and Modeling. - Washington DC : American Chemical Society (ACS). - 1549-9596 .- 1549-960X. ; 58:5, s. 1132-1140
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Tidskriftsartikel (refereegranskat)abstract
- Making predictions with an associated confidence is highly desirable as it facilitates decision making and resource prioritization. Conformal regression is a machine learning framework that allows the user to define the required confidence and delivers predictions that are guaranteed to be correct to the selected extent. In this study, we apply conformal regression to model molecular properties and bioactivity values and investigate different ways to scale the outputted prediction intervals to create as efficient (i.e. narrow) regressors as possible. Different algorithms to estimate the prediction uncertainty were used to normalize the prediction ranges and the different approaches were evaluated on 29 publicly available datasets. Our results show that the most efficient conformal regressors are obtained when using the natural exponential of the ensemble standard deviation from the underlying random forest to scale the prediction intervals. This approach afforded an average prediction range of 1.65 pIC50 units at the 80 % confidence level when applied to bioactivity modeling. The choice of nonconformity function has a pronounced impact on the average prediction range with a difference of close to one log unit in bioactivity between the tightest and widest prediction range. Overall, conformal regression is a robust approach to generate bioactivity predictions with associated confidence.
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| 30. |
- Svensson, Fredrik, et al.
(författare)
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Improving Screening Efficiency through Iterative Screening Using Docking and Conformal Prediction
- 2017
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Ingår i: Journal of Chemical Information and Modeling. - Washington : American Chemical Society (ACS). - 1549-9596 .- 1549-960X. ; 57:3, s. 439-444
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Tidskriftsartikel (refereegranskat)abstract
- High-throughput screening, where thousands of molecules rapidly can be assessed for activity against a protein, has been the dominating approach in drug discovery for many years. However, these methods are costly and require much time and effort. In order to suggest an improvement to this situation, in this study, we apply an iterative screening process, where an initial set of compounds are selected for screening based on molecular docking. The outcome of the initial screen is then used to classify the remaining compounds through a conformal predictor. The approach was retrospectively validated using 41 targets from the Directory of Useful Decoys, Enhanced (DUD-E), ensuring scaffold diversity among the active compounds. The results show that 57% of the remaining active compounds could be identified while only screening 9.4% of the database. The overall hit rate (7.6%) was also higher than, when using docking alone (5.2%). When limiting the search to the top scored compounds from docking, 39.6% of the active compounds could be identified, compared to 13.5% when screening the same number of compounds solely based on docking. The use of conformal predictors also gives a clear indication of the number of compounds to screen in the next iteration. These results indicate that iterative screening based on molecular docking and conformal prediction can be an efficient way to find active compounds while screening only a small part of the compound collection.
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| 31. |
- Svensson, Fredrik, et al.
(författare)
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Maximizing gain in high-throughput screening using conformal prediction
- 2018
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Ingår i: Journal of Cheminformatics. - London : Chemistry Central. - 1758-2946. ; 10:1
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Tidskriftsartikel (refereegranskat)abstract
- Iterative screening has emerged as a promising approach to increase the efficiency of screening campaigns compared to traditional high throughput approaches. By learning from a subset of the compound library, inferences on what compounds to screen next can be made by predictive models, resulting in more efficient screening. One way to evaluate screening is to consider the cost of screening compared to the gain associated with finding an active compound. In this work, we introduce a conformal predictor coupled with a gain-cost function with the aim to maximise gain in iterative screening. Using this setup we were able to show that by evaluating the predictions on the training data, very accurate predictions on what settings will produce the highest gain on the test data can be made. We evaluate the approach on 12 bioactivity datasets from PubChem training the models using 20% of the data. Depending on the settings of the gain-cost function, the settings generating the maximum gain were accurately identified in 8-10 out of the 12 datasets. Broadly, our approach can predict what strategy generates the highest gain based on the results of the cost-gain evaluation: to screen the compounds predicted to be active, to screen all the remaining data, or not to screen any additional compounds. When the algorithm indicates that the predicted active compounds should be screened, our approach also indicates what confidence level to apply in order to maximize gain. Hence, our approach facilitates decision-making and allocation of the resources where they deliver the most value by indicating in advance the likely outcome of a screening campaign.
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| 32. |
- Svensson, Fredrik, et al.
(författare)
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Modelling compound cytotoxicity using conformal prediction and PubChem HTS data
- 2017
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Ingår i: Toxicology Research. - : Oxford University Press. - 2045-452X .- 2045-4538. ; 6:1, s. 73-80
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Tidskriftsartikel (refereegranskat)abstract
- The assessment of compound cytotoxicity is an important part of the drug discovery process. Accurate predictions of cytotoxicity have the potential to expedite decision making and save considerable time and effort. In this work we apply class conditional conformal prediction to model the cytotoxicity of compounds based on 16 high throughput cytotoxicity assays from PubChem. The data span 16 cell lines and comprise more than 440 000 unique compounds. The data sets are heavily imbalanced with only 0.8% of the tested compounds being cytotoxic. We trained one classification model for each cell line and validated the performance with respect to validity and accuracy. The generated models deliver high quality predictions for both toxic and non-toxic compounds despite the imbalance between the two classes. On external data collected from the same assay provider as one of the investigated cell lines the model had a sensitivity of 74% and a specificity of 65% at the 80% confidence level among the compounds assigned to a single class. Compared to previous approaches for large scale cytotoxicity modelling, this represents a balanced performance in the prediction of the toxic and non-toxic classes. The conformal prediction framework also allows the modeller to control the error frequency of the predictions, allowing predictions of cytotoxicity outcomes with confidence.
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| 33. |
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The Seventeenth Data Release of the Sloan Digital Sky Surveys : Complete Release of MaNGA, MaStar, and APOGEE-2 Data
- 2022
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Ingår i: Astrophysical Journal Supplement Series. - : Institute of Physics (IOP). - 0067-0049 .- 1538-4365. ; 259:2
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Tidskriftsartikel (refereegranskat)abstract
- This paper documents the seventeenth data release (DR17) from the Sloan Digital Sky Surveys; the fifth and final release from the fourth phase (SDSS-IV). DR17 contains the complete release of the Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey, which reached its goal of surveying over 10,000 nearby galaxies. The complete release of the MaNGA Stellar Library accompanies this data, providing observations of almost 30,000 stars through the MaNGA instrument during bright time. DR17 also contains the complete release of the Apache Point Observatory Galactic Evolution Experiment 2 survey that publicly releases infrared spectra of over 650,000 stars. The main sample from the Extended Baryon Oscillation Spectroscopic Survey (eBOSS), as well as the subsurvey Time Domain Spectroscopic Survey data were fully released in DR16. New single-fiber optical spectroscopy released in DR17 is from the SPectroscipic IDentification of ERosita Survey subsurvey and the eBOSS-RM program. Along with the primary data sets, DR17 includes 25 new or updated value-added catalogs. This paper concludes the release of SDSS-IV survey data. SDSS continues into its fifth phase with observations already underway for the Milky Way Mapper, Local Volume Mapper, and Black Hole Mapper surveys.
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| 34. |
- Verder, Henrik, et al.
(författare)
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Early Surfactant Guided by Lamellar Body Counts on Gastric Aspirate in Very Preterm Infants
- 2013
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Ingår i: Neonatology. - : S. Karger AG. - 1661-7800 .- 1661-7819. ; 104:2, s. 116-122
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Tidskriftsartikel (refereegranskat)abstract
- Background: We have developed a rapid method, based on lamellar body counts (LBC) on gastric aspirate, for identifying newborns who will develop respiratory distress syndrome with a need for surfactant supplementation. Objective: We set out to test whether it was possible to improve the outcome when used in a clinical trial. Methods: We randomly assigned 380 infants born at 24-29 weeks' gestation and supported with nasal continuous positive airway pressure (nCPAP) to receive surfactant guided either by LBC (intervention group) or increasing need for oxygen (control group). The primary outcome was mechanical ventilation or death within 5 days. Secondary outcomes included need for oxygen expressed by arterial to alveolar oxygen tension ratio (a/APO(2)) at the age of 6 h and need for oxygen at day 28. Results: The primary outcomes were equal (25%) in the two groups. The intervention group had higher a/APO(2) than the control group at 6 h, median 0.64 versus 0.52 (p < 0.01), and the subgroup with gestational age 26-29 weeks needed fewer days of oxygen supplementation than the controls, median 2 vs. 9 days (p = 0.01), and fewer infants needed oxygen at day 28 (p = 0.04). Furthermore, there was a tendency in the intervention group towards a shorter duration of nCPAP. Too little or viscose aspirate in 23% of the cases was a limitation of the method. Conclusion: Using LBC test as indicator of lung maturity and early surfactant therapy in very preterm newborns, it is possible to reduce the need for oxygen supplementation. Copyright (C) 2013 S. Karger AG, Basel
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| 35. |
- Wang, Haidong, et al.
(författare)
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Global, regional, and national life expectancy, all-cause mortality, and cause-specific mortality for 249 causes of death, 1980-2015 : a systematic analysis for the Global Burden of Disease Study 2015
- 2016
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Ingår i: The Lancet. - 0140-6736 .- 1474-547X. ; 388:10053, s. 1459-1544
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Improving survival and extending the longevity of life for all populations requires timely, robust evidence on local mortality levels and trends. The Global Burden of Disease 2015 Study (GBD 2015) provides a comprehensive assessment of all-cause and cause-specific mortality for 249 causes in 195 countries and territories from 1980 to 2015. These results informed an in-depth investigation of observed and expected mortality patterns based on sociodemographic measures.METHODS: We estimated all-cause mortality by age, sex, geography, and year using an improved analytical approach originally developed for GBD 2013 and GBD 2010. Improvements included refinements to the estimation of child and adult mortality and corresponding uncertainty, parameter selection for under-5 mortality synthesis by spatiotemporal Gaussian process regression, and sibling history data processing. We also expanded the database of vital registration, survey, and census data to 14 294 geography-year datapoints. For GBD 2015, eight causes, including Ebola virus disease, were added to the previous GBD cause list for mortality. We used six modelling approaches to assess cause-specific mortality, with the Cause of Death Ensemble Model (CODEm) generating estimates for most causes. We used a series of novel analyses to systematically quantify the drivers of trends in mortality across geographies. First, we assessed observed and expected levels and trends of cause-specific mortality as they relate to the Socio-demographic Index (SDI), a summary indicator derived from measures of income per capita, educational attainment, and fertility. Second, we examined factors affecting total mortality patterns through a series of counterfactual scenarios, testing the magnitude by which population growth, population age structures, and epidemiological changes contributed to shifts in mortality. Finally, we attributed changes in life expectancy to changes in cause of death. We documented each step of the GBD 2015 estimation processes, as well as data sources, in accordance with Guidelines for Accurate and Transparent Health Estimates Reporting (GATHER).FINDINGS: Globally, life expectancy from birth increased from 61·7 years (95% uncertainty interval 61·4-61·9) in 1980 to 71·8 years (71·5-72·2) in 2015. Several countries in sub-Saharan Africa had very large gains in life expectancy from 2005 to 2015, rebounding from an era of exceedingly high loss of life due to HIV/AIDS. At the same time, many geographies saw life expectancy stagnate or decline, particularly for men and in countries with rising mortality from war or interpersonal violence. From 2005 to 2015, male life expectancy in Syria dropped by 11·3 years (3·7-17·4), to 62·6 years (56·5-70·2). Total deaths increased by 4·1% (2·6-5·6) from 2005 to 2015, rising to 55·8 million (54·9 million to 56·6 million) in 2015, but age-standardised death rates fell by 17·0% (15·8-18·1) during this time, underscoring changes in population growth and shifts in global age structures. The result was similar for non-communicable diseases (NCDs), with total deaths from these causes increasing by 14·1% (12·6-16·0) to 39·8 million (39·2 million to 40·5 million) in 2015, whereas age-standardised rates decreased by 13·1% (11·9-14·3). Globally, this mortality pattern emerged for several NCDs, including several types of cancer, ischaemic heart disease, cirrhosis, and Alzheimer's disease and other dementias. By contrast, both total deaths and age-standardised death rates due to communicable, maternal, neonatal, and nutritional conditions significantly declined from 2005 to 2015, gains largely attributable to decreases in mortality rates due to HIV/AIDS (42·1%, 39·1-44·6), malaria (43·1%, 34·7-51·8), neonatal preterm birth complications (29·8%, 24·8-34·9), and maternal disorders (29·1%, 19·3-37·1). Progress was slower for several causes, such as lower respiratory infections and nutritional deficiencies, whereas deaths increased for others, including dengue and drug use disorders. Age-standardised death rates due to injuries significantly declined from 2005 to 2015, yet interpersonal violence and war claimed increasingly more lives in some regions, particularly in the Middle East. In 2015, rotaviral enteritis (rotavirus) was the leading cause of under-5 deaths due to diarrhoea (146 000 deaths, 118 000-183 000) and pneumococcal pneumonia was the leading cause of under-5 deaths due to lower respiratory infections (393 000 deaths, 228 000-532 000), although pathogen-specific mortality varied by region. Globally, the effects of population growth, ageing, and changes in age-standardised death rates substantially differed by cause. Our analyses on the expected associations between cause-specific mortality and SDI show the regular shifts in cause of death composition and population age structure with rising SDI. Country patterns of premature mortality (measured as years of life lost [YLLs]) and how they differ from the level expected on the basis of SDI alone revealed distinct but highly heterogeneous patterns by region and country or territory. Ischaemic heart disease, stroke, and diabetes were among the leading causes of YLLs in most regions, but in many cases, intraregional results sharply diverged for ratios of observed and expected YLLs based on SDI. Communicable, maternal, neonatal, and nutritional diseases caused the most YLLs throughout sub-Saharan Africa, with observed YLLs far exceeding expected YLLs for countries in which malaria or HIV/AIDS remained the leading causes of early death.INTERPRETATION: At the global scale, age-specific mortality has steadily improved over the past 35 years; this pattern of general progress continued in the past decade. Progress has been faster in most countries than expected on the basis of development measured by the SDI. Against this background of progress, some countries have seen falls in life expectancy, and age-standardised death rates for some causes are increasing. Despite progress in reducing age-standardised death rates, population growth and ageing mean that the number of deaths from most non-communicable causes are increasing in most countries, putting increased demands on health systems.
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| 36. |
- Aad, G., et al.
(författare)
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- 2015
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Ingår i: Physical Review C (Nuclear Physics). - 0556-2813 .- 1089-490X. ; 92:3
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Tidskriftsartikel (refereegranskat)
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| 37. |
- Aad, G., et al.
(författare)
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- 2015
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Ingår i: Physical Review C (Nuclear Physics). - 0556-2813 .- 1089-490X. ; 92:3
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Tidskriftsartikel (refereegranskat)
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| 38. |
- Aad, G., et al.
(författare)
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- 2015
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Tidskriftsartikel (refereegranskat)
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| 39. |
- Aad, G., et al.
(författare)
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- 2015
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Ingår i: Physical Review D (Particles, Fields, Gravitation and Cosmology). - 1550-2368 .- 1550-7998. ; 91:11, s. 112011-
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Tidskriftsartikel (refereegranskat)
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| 40. |
- Aad, G., et al.
(författare)
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- 2015
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Ingår i: Physical Review Letters. - 1079-7114 .- 0031-9007. ; 115:9
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Tidskriftsartikel (refereegranskat)
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| 41. |
- Aad, G., et al.
(författare)
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- 2015
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Ingår i: Journal of High Energy Physics. - : Springer-Verlag New York. - 1029-8479 .- 1126-6708. ; :9
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Tidskriftsartikel (refereegranskat)
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| 42. |
- Aad, G., et al.
(författare)
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- 2015
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Ingår i: Physical Review D (Particles, Fields, Gravitation and Cosmology). - 1550-2368 .- 1550-7998. ; 92:1
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Tidskriftsartikel (refereegranskat)
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| 43. |
- Aad, G., et al.
(författare)
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- 2015
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Ingår i: Physical Review Letters. - : American Physical Society. - 1079-7114 .- 0031-9007. ; 114:22
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Tidskriftsartikel (refereegranskat)
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| 44. |
- Aad, G., et al.
(författare)
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- 2015
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Ingår i: Journal of High Energy Physics. - 1029-8479 .- 1126-6708. ; :8
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Tidskriftsartikel (refereegranskat)
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| 45. |
- Aad, G., et al.
(författare)
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- 2015
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Ingår i: Physical Review D (Particles, Fields, Gravitation and Cosmology). - 1550-2368 .- 1550-7998. ; 92:9
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Tidskriftsartikel (refereegranskat)
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| 46. |
- Aad, G., et al.
(författare)
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- 2015
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Ingår i: Physical Review Letters. - 1079-7114 .- 0031-9007. ; 115:13
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Tidskriftsartikel (refereegranskat)
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| 47. |
- Aad, G., et al.
(författare)
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- 2015
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Tidskriftsartikel (refereegranskat)
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| 48. |
- Aad, G., et al.
(författare)
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- 2015
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Tidskriftsartikel (refereegranskat)
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| 49. |
- Aad, G., et al.
(författare)
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- 2015
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Ingår i: Physical Review Letters. - 1079-7114 .- 0031-9007. ; 115:3
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Tidskriftsartikel (refereegranskat)
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