| 1. |
- Faber, Zachary J, et al.
(författare)
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The genomic landscape of core-binding factor acute myeloid leukemias
- 2016
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Ingår i: Nature Genetics. - : Springer Science and Business Media LLC. - 1546-1718 .- 1061-4036. ; 48, s. 1551-1556
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Tidskriftsartikel (refereegranskat)abstract
- Acute myeloid leukemia (AML) comprises a heterogeneous group of leukemias frequently defined by recurrent cytogenetic abnormalities, including rearrangements involving the core-binding factor (CBF) transcriptional complex. To better understand the genomic landscape of CBF-AMLs, we analyzed both pediatric (n = 87) and adult (n = 78) samples, including cases with RUNX1-RUNX1T1 (n = 85) or CBFB-MYH11 (n = 80) rearrangements, by whole-genome or whole-exome sequencing. In addition to known mutations in the Ras pathway, we identified recurrent stabilizing mutations in CCND2, suggesting a previously unappreciated cooperating pathway in CBF-AML. Outside of signaling alterations, RUNX1-RUNX1T1 and CBFB-MYH11 AMLs demonstrated remarkably different spectra of cooperating mutations, as RUNX1-RUNX1T1 cases harbored recurrent mutations in DHX15 and ZBTB7A, as well as an enrichment of mutations in epigenetic regulators, including ASXL2 and the cohesin complex. This detailed analysis provides insights into the pathogenesis and development of CBF-AML, while highlighting dramatic differences in the landscapes of cooperating mutations for these related AML subtypes.
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| 2. |
- Andersson, Anna, et al.
(författare)
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The landscape of somatic mutations in infant MLL-rearranged acute lymphoblastic leukemias.
- 2015
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Ingår i: Nature Genetics. - : Springer Science and Business Media LLC. - 1546-1718 .- 1061-4036. ; 47:4, s. 192-330
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Tidskriftsartikel (refereegranskat)abstract
- Infant acute lymphoblastic leukemia (ALL) with MLL rearrangements (MLL-R) represents a distinct leukemia with a poor prognosis. To define its mutational landscape, we performed whole-genome, exome, RNA and targeted DNA sequencing on 65 infants (47 MLL-R and 18 non-MLL-R cases) and 20 older children (MLL-R cases) with leukemia. Our data show that infant MLL-R ALL has one of the lowest frequencies of somatic mutations of any sequenced cancer, with the predominant leukemic clone carrying a mean of 1.3 non-silent mutations. Despite this paucity of mutations, we detected activating mutations in kinase-PI3K-RAS signaling pathway components in 47% of cases. Surprisingly, these mutations were often subclonal and were frequently lost at relapse. In contrast to infant cases, MLL-R leukemia in older children had more somatic mutations (mean of 6.5 mutations/case versus 1.3 mutations/case, P = 7.15 × 10(-5)) and had frequent mutations (45%) in epigenetic regulators, a category of genes that, with the exception of MLL, was rarely mutated in infant MLL-R ALL.
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| 3. |
- Agudelo, Leandro Z., et al.
(författare)
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Metabolic resilience is encoded in genome plasticity
- 2021
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- Metabolism plays a central role in evolution, as resource conservation is a selective pressure for fitness and survival.Resource-driven adaptations offer a good model to study evolutionary innovation more broadly. It remains unknown howresource-driven optimization of genome function integrates chromatin architecture with transcriptional phase transitions.Here we show that tuning of genome architecture and heterotypic transcriptional condensates mediate resilience tonutrient limitation. Network genomic integration of phenotypic, structural, and functional relationships reveals that fattissue promotes organismal adaptations through metabolic acceleration chromatin domains and heterotypic PGC1Acondensates. We find evolutionary adaptations in several dimensions; low conservation of amino acid residues withinprotein disorder regions, nonrandom chromatin location of metabolic acceleration domains, condensate-chromatin stabilitythrough cis-regulatory anchoring and encoding of genome plasticity in radial chromatin organization. We show thatenvironmental tuning of these adaptations leads to fasting endurance, through efficient nuclear compartmentalization oflipid metabolic regions, and, locally, human-specific burst kinetics of lipid cycling genes. This process reduces oxidativestress, and fatty-acid mediated cellular acidification, enabling endurance of condensate chromatin conformations.Comparative genomics of genetic and diet perturbations reveal mammalian convergence of phenotype and structuralrelationships, along with loss of transcriptional control by diet-induced obesity. Further, we find that radial transcriptionalorganization is encoded in functional divergence of metabolic disease variant-hubs, heterotypic condensate composition,and protein residues sensing metabolic variation. During fuel restriction, these features license the formation of largeheterotypic condensates that buffer proton excess, and shift viscoelasticity for condensate endurance. This mechanismmaintains physiological pH, reduces pH-resilient inflammatory gene programs, and enables genome plasticity throughtranscriptionally driven cell-specific chromatin contacts. In vivo manipulation of this circuit promotes fasting-likeadaptations with heterotypic nuclear compartments, metabolic and cell-specific homeostasis. In sum, we uncover here ageneral principle by which transcription uses environmental fluctuations for genome function, and demonstrate howresource conservation optimizes transcriptional self-organization through robust feedback integrators, highlighting obesityas an inhibitor of genome plasticity relevant for many diseases.
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| 4. |
- Li, Y. Q., et al.
(författare)
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CRNNTL: Convolutional Recurrent Neural Network and Transfer Learning for QSAR Modeling in Organic Drug and Material Discovery
- 2021
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Ingår i: Molecules. - : MDPI AG. - 1420-3049. ; 26:23
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Tidskriftsartikel (refereegranskat)abstract
- Molecular latent representations, derived from autoencoders (AEs), have been widely used for drug or material discovery over the past couple of years. In particular, a variety of machine learning methods based on latent representations have shown excellent performance on quantitative structure-activity relationship (QSAR) modeling. However, the sequence feature of them has not been considered in most cases. In addition, data scarcity is still the main obstacle for deep learning strategies, especially for bioactivity datasets. In this study, we propose the convolutional recurrent neural network and transfer learning (CRNNTL) method inspired by the applications of polyphonic sound detection and electrocardiogram classification. Our model takes advantage of both convolutional and recurrent neural networks for feature extraction, as well as the data augmentation method. According to QSAR modeling on 27 datasets, CRNNTL can outperform or compete with state-of-art methods in both drug and material properties. In addition, the performances on one isomers-based dataset indicate that its excellent performance results from the improved ability in global feature extraction when the ability of the local one is maintained. Then, the transfer learning results show that CRNNTL can overcome data scarcity when choosing relative source datasets. Finally, the high versatility of our model is shown by using different latent representations as inputs from other types of AEs.
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| 5. |
- Yongjin, Zhang, et al.
(författare)
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Copula-based reliability analysis for a parallel system with a cold standby
- 2018
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Ingår i: Communications in Statistics - Theory and Methods. - : Taylor and Francis Inc.. - 0361-0926 .- 1532-415X. ; 47:3, s. 562-582
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Tidskriftsartikel (refereegranskat)abstract
- The traditional reliability models cannot well reflect the effect of performance dependence of subsystems on the reliability of system, and neglect the problems of initial reliability and standby redundancy. In this paper, the reliability of a parallel system with active multicomponents and a single cold-standby unit has been investigated. The simultaneously working components are dependent and the dependence is expressed by a copula function. Based on the theories of conditional probability, the explicit expressions for the reliability and the MTTF of the system, in terms of the copula function and marginal lifetime distributions, are obtained. Let the copula function be the FGM copula and the marginal lifetime distribution be exponential distribution, a system with two parallel dependent units and a single cold-standby unit is taken as an example. The effect of different degrees of dependence among components on system reliability is analyzed, and the system reliability can be expressed as the linear combination of exponential reliability functions with different failure rates. For investigating how the degree of dependence affects the mean lifetime, furthermore, the parallel system with a single cold standby, comprising different number of active components, is also presented. The effectiveness of the modeling method is verified, and the method presented provides a theoretical basis for reliability design of engineering systems and physics of failure.
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