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叶凯，1977年生，教授，博士生导师，入选西安交通大学青年拔尖人才计划A类。2008年获荷兰莱顿大学博士学位，2008-2009年欧洲生物信息学研究所（英国）博士后，2009-2012年荷兰莱顿大学助理教授，2012-2016年美国圣路易斯华盛顿大学助理教授，2016年入职西安交通大学，现任“叶凯青年科学家工作室”负责人。研究方向：生物医学大数据的深度挖掘方法和应用。
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学者姓名：叶凯
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| GB/T 7714 | Reyna, M.A. , Haan, D. , Paczkowska, M. et al. Author Correction: Pathway and network analysis of more than 2500 whole cancer genomes (Nature Communications, (2020), 11, 1, (729), 10.1038/s41467-020-14367-0) [未知]. |
| MLA | Reyna, M.A. et al. "Author Correction: Pathway and network analysis of more than 2500 whole cancer genomes (Nature Communications, (2020), 11, 1, (729), 10.1038/s41467-020-14367-0)" [未知]. |
| APA | Reyna, M.A. , Haan, D. , Paczkowska, M. , Verbeke, L.P.C. , Vazquez, M. , Kahraman, A. et al. Author Correction: Pathway and network analysis of more than 2500 whole cancer genomes (Nature Communications, (2020), 11, 1, (729), 10.1038/s41467-020-14367-0) [未知]. |
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In the published version of this paper, the members of the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortiumwere listed in the Supplementary Information; however, these members shouldhave been included in themainpaper.The originalArticle has been corrected to include the members and affiliations of the PCAWG Consortium in the main paper; the corrections have been made to the HTML version of the Article but not the PDF version. Additional corrections to affiliations and author names have been made to the PDF and HTML versions of the original Article for consistency of information between the PCAWG list and the main paper. © The Author(s) 2022.
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| GB/T 7714 | Rubanova, Y. , Shi, R. , Harrigan, C.F. et al. Author Correction: Reconstructing evolutionary trajectories of mutation signature activities in cancer using TrackSig (Nature Communications, (2020), 11, 1, (731), 10.1038/s41467-020-14352-7) [未知]. |
| MLA | Rubanova, Y. et al. "Author Correction: Reconstructing evolutionary trajectories of mutation signature activities in cancer using TrackSig (Nature Communications, (2020), 11, 1, (731), 10.1038/s41467-020-14352-7)" [未知]. |
| APA | Rubanova, Y. , Shi, R. , Harrigan, C.F. , Li, R. , Wintersinger, J. , Sahin, N. et al. Author Correction: Reconstructing evolutionary trajectories of mutation signature activities in cancer using TrackSig (Nature Communications, (2020), 11, 1, (731), 10.1038/s41467-020-14352-7) [未知]. |
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Abstract ：
In the published version of this paper, the members of the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortiumwere listed in the Supplementary Information; however, these members shouldhave been included in themainpaper.The originalArticle has been corrected to include the members and affiliations of the PCAWG Consortium in the main paper; the corrections have been made to the HTML version of the Article but not the PDF version. Additional corrections to affiliations and author names have been made to the PDF and HTML versions of the original Article for consistency of information between the PCAWG list and the main paper. © The Author(s) 2022.
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| GB/T 7714 | Jiao, W. , Atwal, G. , Polak, P. et al. Author Correction: A deep learning system accurately classifies primary and metastatic cancers using passenger mutation patterns (Nature Communications, (2020), 11, 1, (728), 10.1038/s41467-019-13825-8) [未知]. |
| MLA | Jiao, W. et al. "Author Correction: A deep learning system accurately classifies primary and metastatic cancers using passenger mutation patterns (Nature Communications, (2020), 11, 1, (728), 10.1038/s41467-019-13825-8)" [未知]. |
| APA | Jiao, W. , Atwal, G. , Polak, P. , Karlic, R. , Cuppen, E. , Al-Shahrour, F. et al. Author Correction: A deep learning system accurately classifies primary and metastatic cancers using passenger mutation patterns (Nature Communications, (2020), 11, 1, (728), 10.1038/s41467-019-13825-8) [未知]. |
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Abstract ：
In the published version of this paper, the members of the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortiumwere listed in the Supplementary Information; however, these members shouldhave been included in themainpaper.The originalArticle has been corrected to include the members and affiliations of the PCAWG Consortium in the main paper; the corrections have been made to the HTML version of the Article but not the PDF version. Additional corrections to affiliations have been made to the PDF and HTML versions of the original Article for consistency of information between the PCAWG list and the main paper. © The Author(s) 2022.
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| GB/T 7714 | Sieverling, L. , Hong, C. , Koser, S.D. et al. Author Correction: Genomic footprints of activated telomere maintenance mechanisms in cancer (Nature Communications, (2020), 11, 1, (733), 10.1038/s41467-019-13824-9) [未知]. |
| MLA | Sieverling, L. et al. "Author Correction: Genomic footprints of activated telomere maintenance mechanisms in cancer (Nature Communications, (2020), 11, 1, (733), 10.1038/s41467-019-13824-9)" [未知]. |
| APA | Sieverling, L. , Hong, C. , Koser, S.D. , Ginsbach, P. , Kleinheinz, K. , Hutter, B. et al. Author Correction: Genomic footprints of activated telomere maintenance mechanisms in cancer (Nature Communications, (2020), 11, 1, (733), 10.1038/s41467-019-13824-9) [未知]. |
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Abstract ：
In the published version of this paper, the members of the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortiumwere listed in the Supplementary Information; however, these members shouldhave been included in themainpaper.The originalArticle has been corrected to include the members and affiliations of the PCAWG Consortium in the main paper; the corrections have been made to the HTML version of the Article but not the PDF version. In the PCAWG Transcriptome Working Group, the affiliation ‘BioForA, French National Institute for Agriculture, Food, and Environment (INRAE),ONF,Orléans, France’ for Aurélien Chateignerwas alsomissing. The original Article has been corrected. Additional corrections to affiliations have been made to the PDF and HTML versions of the original Article for consistency of information between the PCAWG list and the main paper. © The Author(s) 2022.
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| GB/T 7714 | Zhang, Y. , Chen, F. , Fonseca, N.A. et al. Author Correction: High-coverage whole-genome analysis of 1220 cancers reveals hundreds of genes deregulated by rearrangement-mediated cis-regulatory alterations (Nature Communications, (2020), 11, 1, (736), 10.1038/s41467-019-13885-w) [未知]. |
| MLA | Zhang, Y. et al. "Author Correction: High-coverage whole-genome analysis of 1220 cancers reveals hundreds of genes deregulated by rearrangement-mediated cis-regulatory alterations (Nature Communications, (2020), 11, 1, (736), 10.1038/s41467-019-13885-w)" [未知]. |
| APA | Zhang, Y. , Chen, F. , Fonseca, N.A. , He, Y. , Fujita, M. , Nakagawa, H. et al. Author Correction: High-coverage whole-genome analysis of 1220 cancers reveals hundreds of genes deregulated by rearrangement-mediated cis-regulatory alterations (Nature Communications, (2020), 11, 1, (736), 10.1038/s41467-019-13885-w) [未知]. |
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Abstract ：
In the published version of this paper, the members of the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortiumwere listed in the Supplementary Information; however, these members should have been included in themain paper. The original article has been corrected to include the members and affiliations of the PCAWG Consortium in the main paper; the corrections have been made to the HTML version of the article but not the PDF version. © The Author(s) 2022.
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| GB/T 7714 | Cmero, M. , Yuan, K. , Ong, C.S. et al. Author Correction: Inferring structural variant cancer cell fraction (Nature Communications, (2020), 11, 1, (730), 10.1038/s41467-020-14351-8) [未知]. |
| MLA | Cmero, M. et al. "Author Correction: Inferring structural variant cancer cell fraction (Nature Communications, (2020), 11, 1, (730), 10.1038/s41467-020-14351-8)" [未知]. |
| APA | Cmero, M. , Yuan, K. , Ong, C.S. , Schröder, J. , Adams, D.J. , Anur, P. et al. Author Correction: Inferring structural variant cancer cell fraction (Nature Communications, (2020), 11, 1, (730), 10.1038/s41467-020-14351-8) [未知]. |
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Abstract ：
In the published version of this paper, the members of the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortiumwere listed in the Supplementary Information; however, these members shouldhave been included in themainpaper.The originalArticle has been corrected to include the members and affiliations of the PCAWG Consortium in the main paper; the corrections have been made to the HTML version of the Article but not the PDF version. Additional minor corrections to affiliations have been made to the PDF and HTML versions of the original Article for consistency of information between the PCAWG list and themain paper. © The Author(s) 2022.
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| GB/T 7714 | Bhandari, V. , Li, C.H. , Bristow, R.G. et al. Author Correction: Divergent mutational processes distinguish hypoxic and normoxic tumours (Nature Communications, (2020), 11, 1, (737), 10.1038/s41467-019-14052-x) [未知]. |
| MLA | Bhandari, V. et al. "Author Correction: Divergent mutational processes distinguish hypoxic and normoxic tumours (Nature Communications, (2020), 11, 1, (737), 10.1038/s41467-019-14052-x)" [未知]. |
| APA | Bhandari, V. , Li, C.H. , Bristow, R.G. , Boutros, P.C. , Aaltonen, L.A. , Abascal, F. et al. Author Correction: Divergent mutational processes distinguish hypoxic and normoxic tumours (Nature Communications, (2020), 11, 1, (737), 10.1038/s41467-019-14052-x) [未知]. |
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In polypharmacology drugs are required to bind to multiple specific targets, for example to enhance efficacy or to reduce resistance formation. Although deep learning has achieved a breakthrough in de novo design in drug discovery, most of its applications only focus on a single drug target to generate drug-like active molecules. However, in reality drug molecules often interact with more than one target which can have desired (polypharmacology) or undesired (toxicity) effects. In a previous study we proposed a new method named DrugEx that integrates an exploration strategy into RNN-based reinforcement learning to improve the diversity of the generated molecules. Here, we extended our DrugEx algorithm with multi-objective optimization to generate drug-like molecules towards multiple targets or one specific target while avoiding off-targets (the two adenosine receptors, A(1)AR and A(2A)AR, and the potassium ion channel hERG in this study). In our model, we applied an RNN as the agent and machine learning predictors as the environment. Both the agent and the environment were pre-trained in advance and then interplayed under a reinforcement learning framework. The concept of evolutionary algorithms was merged into our method such that crossover and mutation operations were implemented by the same deep learning model as the agent. During the training loop, the agent generates a batch of SMILES-based molecules. Subsequently scores for all objectives provided by the environment are used to construct Pareto ranks of the generated molecules. For this ranking a non-dominated sorting algorithm and a Tanimoto-based crowding distance algorithm using chemical fingerprints are applied. Here, we adopted GPU acceleration to speed up the process of Pareto optimization. The final reward of each molecule is calculated based on the Pareto ranking with the ranking selection algorithm. The agent is trained under the guidance of the reward to make sure it can generate desired molecules after convergence of the training process. All in all we demonstrate generation of compounds with a diverse predicted selectivity profile towards multiple targets, offering the potential of high efficacy and low toxicity.
Keyword ：
Adenosine receptors Cheminformatics Deep learning Exploration strategy Multi-objective optimization Reinforcement learning
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| GB/T 7714 | Liu, Xuhan , Ye, Kai , van Vlijmen, Herman W. T. et al. DrugEx v2: de novo design of drug molecules by Pareto-based multi-objective reinforcement learning in polypharmacology [J]. | JOURNAL OF CHEMINFORMATICS , 2021 , 13 (1) . |
| MLA | Liu, Xuhan et al. "DrugEx v2: de novo design of drug molecules by Pareto-based multi-objective reinforcement learning in polypharmacology" . | JOURNAL OF CHEMINFORMATICS 13 . 1 (2021) . |
| APA | Liu, Xuhan , Ye, Kai , van Vlijmen, Herman W. T. , Emmerich, Michael T. M. , IJzerman, Adriaan P. , van Westen, Gerard J. P. . DrugEx v2: de novo design of drug molecules by Pareto-based multi-objective reinforcement learning in polypharmacology . | JOURNAL OF CHEMINFORMATICS , 2021 , 13 (1) . |
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Long-read and strand-specific sequencing technologies together facilitate the de novo assembly of high-quality haplotype-resolved human genomes without parent-child trio data. We present 64 assembled haplotypes from 32 diverse human genomes. These highly contiguous haplotype assemblies (average minimum contig length needed to cover 50% of the genome: 26 million base pairs) integrate all forms of genetic variation, even across complex loci. We identified 107,590 structural variants (SVs), of which 68% were not discovered with short-read sequencing, and 278 SV hotspots (spanning megabases of gene-rich sequence). We characterized 130 of the most active mobile element source elements and found that 63% of all SVs arise through homology-mediated mechanisms. This resource enables reliable graph-based genotyping from short reads of up to 50,340 SVs, resulting in the identification of 1526 expression quantitative trait loci as well as SV candidates for adaptive selection within the human population.
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| GB/T 7714 | Ebert, Peter , Audano, Peter A. , Zhu, Qihui et al. Haplotype-resolved diverse human genomes and integrated analysis of structural variation [J]. | SCIENCE , 2021 , 372 (6537) : 48-+ . |
| MLA | Ebert, Peter et al. "Haplotype-resolved diverse human genomes and integrated analysis of structural variation" . | SCIENCE 372 . 6537 (2021) : 48-+ . |
| APA | Ebert, Peter , Audano, Peter A. , Zhu, Qihui , Rodriguez-Martin, Bernardo , Porubsky, David , Bonder, Marc Jan et al. Haplotype-resolved diverse human genomes and integrated analysis of structural variation . | SCIENCE , 2021 , 372 (6537) , 48-+ . |
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Graves' orbitopathy (GO), the most severe manifestation of Graves' hyperthyroidism (GH), is an autoimmune-mediated inflammatory disorder, and treatments often exhibit a low efficacy. CD4+ T cells have been reported to play vital roles in GO progression. To explore the pathogenic CD4+ T cell types that drive GO progression, we applied single-cell RNA sequencing (scRNA-Seq), T cell receptor sequencing (TCR-Seq), flow cytometry, immunofluorescence and mixed lymphocyte reaction (MLR) assays to evaluate CD4+ T cells from GO and GH patients. scRNA-Seq revealed the novel GO-specific cell type CD4+ cytotoxic T lymphocytes (CTLs), which are characterized by chemotactic and inflammatory features. The clonal expansion of this CD4+ CTL population, as demonstrated by TCR-Seq, along with their strong cytotoxic response to autoantigens, localization in orbital sites, and potential relationship with disease relapse provide strong evidence for the pathogenic roles of GZMB and IFN-gamma-secreting CD4+ CTLs in GO. Therefore, cytotoxic pathways may become potential therapeutic targets for GO.
Keyword ：
CD4+cytotoxic T lymphocytes Graves' orbitopathy single-cell RNA sequencing
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| GB/T 7714 | Wang, Yue , Chen, Ziyi , Wang, Tingjie et al. A novel CD4+CTL subtype characterized by chemotaxis and inflammation is involved in the pathogenesis of Graves' orbitopathy [J]. | CELLULAR & MOLECULAR IMMUNOLOGY , 2021 , 18 (3) : 735-745 . |
| MLA | Wang, Yue et al. "A novel CD4+CTL subtype characterized by chemotaxis and inflammation is involved in the pathogenesis of Graves' orbitopathy" . | CELLULAR & MOLECULAR IMMUNOLOGY 18 . 3 (2021) : 735-745 . |
| APA | Wang, Yue , Chen, Ziyi , Wang, Tingjie , Guo, Hui , Liu, Yufeng , Dang, Ningxin et al. A novel CD4+CTL subtype characterized by chemotaxis and inflammation is involved in the pathogenesis of Graves' orbitopathy . | CELLULAR & MOLECULAR IMMUNOLOGY , 2021 , 18 (3) , 735-745 . |
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