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| 2. |
- Gustafsson, Oscar, et al.
(författare)
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Long-wavelength infrared quantum-dot based interband photodetectors
- 2011
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Ingår i: Infrared physics & technology. - : Elsevier BV. - 1350-4495 .- 1879-0275. ; 54:3, s. 287-291
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Tidskriftsartikel (refereegranskat)abstract
- We report on the design and fabrication of (Al)GaAs(Sb)/InAs tensile strained quantum-dot (QD) based detector material for thermal infrared imaging applications in the long-wavelength infrared (LWIR) regime. The detection is based on transitions between confined dot states and continuum states in a type-II band lineup, and we therefore refer to it as a dot-to-bulk (D2B) infrared photodetector with expected benefits including long carrier lifetime due to the type-II band alignment, suppressed Shockley-Read-Hall generation-recombination due to the relatively large-bandgap matrix material, inhibited Auger recombination processes due to the tensile strain and epitaxial simplicity. Metal-organic vapor-phase epitaxy was used to grow multiple (Al)GaAs(Sb) QD layers on InAs substrates at different QD nominal thicknesses, compositions, doping conditions and multilayer periods, and the material was characterized using atomic force and transmission electron microscopy, and Fourier-transform infrared absorption spectroscopy. Dot densities up to 1 x 10(11) cm(-2), 1 x 10(12) cm(-2) and 3 x 10(10) cm(-2) were measured for GaAs, AlGaAs and GaAsSb QDs, respectively. Strong absorption in GaAs, AlGaAs and GaAsSb multilayer QD samples was observed in the wavelength range 6-12 mu m. From the wavelength shift in the spectral absorption for samples with varying QD thickness and composition it is believed that the absorption is due to an intra- valance band transition. From this it is possible to estimate the type-II inter-band transition wavelength, thereby suggesting that (Al)GaAs(Sb) QD/InAs heterostructures are suitable candidates for LWIR detection and imaging.
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| 3. |
- Hjelm, M., et al.
(författare)
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New Probabilistic network models and algorithms for oncogenesis
- 2006
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Ingår i: Journal of Computational Biology. - : Mary Ann Liebert Inc. - 1066-5277 .- 1557-8666. ; 13:4, s. 853-865
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Tidskriftsartikel (refereegranskat)abstract
- Chromosomal aberrations in solid tumors appear in complex patterns. It is important to understand how these patterns develop, the dynamics of the process, the temporal or even causal order between aberrations, and the involved pathways. Here we present network models for chromosomal aberrations and algorithms for training models based on observed data. Our models are generative probabilistic models that can be used to study dynamical aspects of chromosomal evolution in cancer cells. They are well suited for a graphical representation that conveys the pathways found in a dataset. By allowing only pairwise dependencies and partition aberrations into modules, in which all aberrations are restricted to have the same dependencies, we reduce the number of parameters so that datasets sizes relevant to cancer applications can be handled. We apply our framework to a dataset of colorectal cancer tumor karyotypes. The obtained model explains the data significantly better than a model where independence between the aberrations is assumed. In fact, the obtained model performs very well with respect to several measures of goodness of fit and is, with respect to repetition of the training, more or less unique.
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| 4. |
- Lauss, Martin, et al.
(författare)
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Robust assignment of cancer subtypes from expression data using a uni-variate gene expression average as classifier
- 2010
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Ingår i: BMC Cancer. - : Springer Science and Business Media LLC. - 1471-2407. ; 10, s. 532-
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Tidskriftsartikel (refereegranskat)abstract
- Background: Genome wide gene expression data is a rich source for the identification of gene signatures suitable for clinical purposes and a number of statistical algorithms have been described for both identification and evaluation of such signatures. Some employed algorithms are fairly complex and hence sensitive to over-fitting whereas others are more simple and straight forward. Here we present a new type of simple algorithm based on ROC analysis and the use of metagenes that we believe will be a good complement to existing algorithms.Results: The basis for the proposed approach is the use of metagenes, instead of collections of individual genes, and a feature selection using AUC values obtained by ROC analysis. Each gene in a data set is assigned an AUC value relative to the tumor class under investigation and the genes are ranked according to these values. Metagenes are then formed by calculating the mean expression level for an increasing number of ranked genes, and the metagene expression value that optimally discriminates tumor classes in the training set is used for classification of new samples. The performance of the metagene is then evaluated using LOOCV and balanced accuracies.Conclusions: We show that the simple uni-variate gene expression average algorithm performs as well as several alternative algorithms such as discriminant analysis and the more complex approaches such as SVM and neural networks. The R package rocc is freely available at http://cran.r-project.org/web/packages/rocc/index.html.
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| 5. |
- Lindgren, David, et al.
(författare)
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Combined Gene Expression and Genomic Profiling Define Two Intrinsic Molecular Subtypes of Urothelial Carcinoma and Gene Signatures for Molecular Grading and Outcome
- 2010
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Ingår i: Cancer Research. - 0008-5472 .- 1538-7445. ; 70:9, s. 3463-3472
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Tidskriftsartikel (refereegranskat)abstract
- In the present investigation, we sought to refine the classification of urothelial carcinoma by combining information on gene expression, genomic, and gene mutation levels. For these purposes, we performed gene expression analysis of 144 carcinomas, and whole genome array-CGH analysis and mutation analyses of FGFR3, PIK3CA, KRAS, HRAS, NRAS, TP53, CDKN2A, and TSC1 in 103 of these cases. Hierarchical cluster analysis identified two intrinsic molecular subtypes, MS1 and MS2, which were validated and defined by the same set of genes in three independent bladder cancer data sets. The two subtypes differed with respect to gene expression and mutation profiles, as well as with the level of genomic instability. The data show that genomic instability was the most distinguishing genomic feature of MS2 tumors, and that this trait was not dependent on TP53/MDM2 alterations. By combining molecular and pathologic data, it was possible to distinguish two molecular subtypes of T(a) and T(1) tumors, respectively. In addition, we define gene signatures validated in two independent data sets that classify urothelial carcinoma into low-grade (G(1)/G(2)) and high-grade (G(3)) tumors as well as non-muscle and muscle-invasive tumors with high precisions and sensitivities, suggesting molecular grading as a relevant complement to standard pathologic grading. We also present a gene expression signature with independent prognostic effect on metastasis and disease-specific survival. We conclude that the combination of molecular and histopathologic classification systems might provide a strong improvement for bladder cancer classification and produce new insights into the development of this tumor type.
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| 6. |
- Martijn, H., et al.
(författare)
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Development of IR imaging at IRnova
- 2009
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Ingår i: Infrared Technology and Applications XXXV. - : SPIE.
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Konferensbidrag (refereegranskat)abstract
- Historically IRnova has exclusively been a company, focused on manufacturing of QWIP detectors. Nowadays, besides continuous improvements of the performance of QWIP FPAs and development of new formats IRnova is involved in development of QWIP detectors for special applications and has started the development of the next generation infrared detectors, as well. In the light of the development of new formats we validate experimentally theoretical calculations of the response of QWIPs for smaller pixel size. These results allow for the development of high performance megapixel QWIP FPA that exhibit the high uniformity and operability QWIP detectors are known for. QWIP is also being considered for space applications. The requirements on dark current and operating temperature are however much more stringent as compared to the terrestrial applications. We show ways to improve the material quality with as a result a higher detector operating temperature. IRnova is also looking at antimony-based strained superlattice material for the LWIR region together with partners at theIMAGIC centre of excellence. One of the ways to overcome the problem with surface currents is passivating overgrowth. We will report the status and results of overgrowing the detector mesas with AlGa(As)Sb in a MOVPE system. At the same centre of excellence a novel material concept is being developed for LWIR detection. This new material contains a superlattice of vertically aligned and electronically coupled InAs and GaSb quantum dots. Simulations show that it should be possible to have LWIR detection in this material. We will present the current status and report results in this research.
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| 7. |
- Tofigh, Ali, et al.
(författare)
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A global structural em algorithm for a model of cancer progression
- 2011
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Ingår i: Adv. Neural Inf. Process. Syst.: Annu. Conf. Neural Inf. Process. Syst., NIPS. - : Neural Information Processing Systems.
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Konferensbidrag (refereegranskat)abstract
- Cancer has complex patterns of progression that include converging as well as diverging progressional pathways. Vogelstein's path model of colon cancer was a pioneering contribution to cancer research. Since then, several attempts have been made at obtaining mathematical models of cancer progression, devising learning algorithms, and applying these to cross-sectional data. Beerenwinkel et al. provided, what they coined, EM-like algorithms for Oncogenetic Trees (OTs) and mixtures of such. Given the small size of current and future data sets, it is important to minimize the number of parameters of a model. For this reason, we too focus on tree-based models and introduce Hidden-variable Oncogenetic Trees (HOTs). In contrast to OTs, HOTs allow for errors in the data and thereby provide more realistic modeling. We also design global structural EM algorithms for learning HOTs and mixtures of HOTs (HOT-mixtures). The algorithms are global in the sense that, during the M-step, they find a structure that yields a global maximum of the expected complete log-likelihood rather than merely one that improves it. The algorithm for single HOTs performs very well on reasonable-sized data sets, while that for HOT-mixtures requires data sets of sizes obtainable only with tomorrow's more cost-efficient technologies.
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| 8. |
- Wang, Q., et al.
(författare)
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Multilayer InAs/InGaAs quantum dot structure grown by MOVPE for optoelectronic device applications
- 2006
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Ingår i: Nanoengineering: Fabrication, Properties, Optics, and Devices III. - : SPIE. ; , s. L3270-L3270
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Konferensbidrag (refereegranskat)abstract
- We report on a quantum dot (QD) structure grown on a 4" GaAs substrate by metal organic vapor phase epitaxy (MOVPE), which consists of five stacked InAs/InGaAs/GaAs QD layers embedded in the center of a typical in-plane waveguide. The density of the QDs is about 2.5 × 1010 cm -2 per QD layer. The photoluminescence (PL) peak wavelength at 1322 nm corresponding to the interband transition of the QD ground states was observed at room temperature with a full width at half-maximum of 49 meV. A good uniformity of the QD structure across the 4" wafer was verified with a variation of the PL peak wavelength of 0.9 % from the wafer center to the edge. Top p-contacts and a bottom n-contact were processed on the QD structure, and electroluminescence (EL) spectra were measured at different temperatures. An EL peak corresponding to the QD ground states emission was obtained at 1325 nm at room temperature.
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| 9. |
- Zhou, Jing, et al.
(författare)
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Initial clustering - a key factor for phase separation kinetics in Fe-Cr-based alloys
- 2014
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Ingår i: Scripta Materialia. - : Elsevier BV. - 1359-6462 .- 1872-8456. ; 75, s. 62-65
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Tidskriftsartikel (refereegranskat)abstract
- Clustering of alloying elements in solution-treated Fe-Cr-based alloys is of considerable importance for their microstructure stability upon aging. The clustering of Cr after solution treatment in three stainless steel alloy categories has been studied by atom probe tomography. Furthermore, phase-field simulations are applied to examine the effect of initial clustering on phase separation evolution. It is concluded that the clustering of Cr found in solution-treated ferritic and duplex alloys plays a critical role in the nanostructure evolution during aging.
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