Zobrazeno 1 - 10
of 68
pro vyhledávání: '"Amin Emad"'
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-18 (2024)
Abstract We introduce GRouNdGAN, a gene regulatory network (GRN)-guided reference-based causal implicit generative model for simulating single-cell RNA-seq data, in silico perturbation experiments, and benchmarking GRN inference methods. Through the
Externí odkaz:
https://doaj.org/article/5220c8a953a4425b89530e3d829429a9
Publikováno v:
Genomics, Proteomics & Bioinformatics, Vol 21, Iss 3, Pp 535-550 (2023)
Prediction of the response of cancer patients to different treatments and identification of biomarkers of drug response are two major goals of individualized medicine. Here, we developed a deep learning framework called TINDL, completely trained on p
Externí odkaz:
https://doaj.org/article/a5a8bc59c73b4a1eb766852882461bc4
Autor:
Chen-Fang Chung, Joan Papillon, José R. Navarro-Betancourt, Julie Guillemette, Ameya Bhope, Amin Emad, Andrey V. Cybulsky
Publikováno v:
Frontiers in Medicine, Vol 10 (2023)
BackgroundHuman glomerulonephritis (GN)—membranous nephropathy (MN), focal segmental glomerulosclerosis (FSGS) and IgA nephropathy (IgAN), as well as diabetic nephropathy (DN) are leading causes of chronic kidney disease. In these glomerulopathies,
Externí odkaz:
https://doaj.org/article/0f84a28e78cc495ea2e2ba9ca816efb5
Publikováno v:
Scientific Reports, Vol 11, Iss 1, Pp 1-12 (2021)
Abstract Identification of transcriptional regulatory mechanisms and signaling networks involved in the response of host cells to infection by SARS-CoV-2 is a powerful approach that provides a systems biology view of gene expression programs involved
Externí odkaz:
https://doaj.org/article/eeca606313dd432f980f57f0858a7731
Autor:
Amin Emad, Saurabh Sinha
Publikováno v:
npj Systems Biology and Applications, Vol 7, Iss 1, Pp 1-14 (2021)
Abstract Reconstruction of transcriptional regulatory networks (TRNs) is a powerful approach to unravel the gene expression programs involved in healthy and disease states of a cell. However, these networks are usually reconstructed independent of th
Externí odkaz:
https://doaj.org/article/03eceeabe2e04f47a265c45458ea358b
Publikováno v:
Scientific Reports, Vol 10, Iss 1, Pp 1-12 (2020)
Abstract The biological processes involved in a drug’s mechanisms of action are oftentimes dynamic, complex and difficult to discern. Time-course gene expression data is a rich source of information that can be used to unravel these complex process
Externí odkaz:
https://doaj.org/article/b3dd2f2679eb403a819f0f7935576ae9
Autor:
Amin Emad, Tania Ray, Tor W. Jensen, Meera Parat, Rachael Natrajan, Saurabh Sinha, Partha S. Ray
Publikováno v:
Breast Cancer Research, Vol 22, Iss 1, Pp 1-13 (2020)
Abstract Background Cancer cells are known to display varying degrees of metastatic propensity, but the molecular basis underlying such heterogeneity remains unclear. Our aims in this study were to (i) elucidate prognostic subtypes in primary tumors
Externí odkaz:
https://doaj.org/article/8c6e3fa75e664d70af70f484a94725e7
Autor:
Jun Ding, David Earl Hostallero, Mohamed Reda El Khili, Gregory Joseph Fonseca, Simon Milette, Nuzha Noorah, Myriam Guay-Belzile, Jonathan Spicer, Noriko Daneshtalab, Martin Sirois, Karine Tremblay, Amin Emad, Simon Rousseau
Publikováno v:
PLoS Computational Biology, Vol 17, Iss 3, p e1008810 (2021)
Abnormal coagulation and an increased risk of thrombosis are features of severe COVID-19, with parallels proposed with hemophagocytic lymphohistiocytosis (HLH), a life-threating condition associated with hyperinflammation. The presence of HLH was des
Externí odkaz:
https://doaj.org/article/663ec620feab4fbaab284ba90f3e62dc
Autor:
Charles Blatti, Amin Emad, Matthew J Berry, Lisa Gatzke, Milt Epstein, Daniel Lanier, Pramod Rizal, Jing Ge, Xiaoxia Liao, Omar Sobh, Mike Lambert, Corey S Post, Jinfeng Xiao, Peter Groves, Aidan T Epstein, Xi Chen, Subhashini Srinivasan, Erik Lehnert, Krishna R Kalari, Liewei Wang, Richard M Weinshilboum, Jun S Song, C Victor Jongeneel, Jiawei Han, Umberto Ravaioli, Nahil Sobh, Colleen B Bushell, Saurabh Sinha
Publikováno v:
PLoS Biology, Vol 18, Iss 1, p e3000583 (2020)
We present Knowledge Engine for Genomics (KnowEnG), a free-to-use computational system for analysis of genomics data sets, designed to accelerate biomedical discovery. It includes tools for popular bioinformatics tasks such as gene prioritization, sa
Externí odkaz:
https://doaj.org/article/95bcc327ce954baea159ae0298bd6085
Publikováno v:
PLoS Computational Biology, Vol 16, Iss 1, p e1007607 (2020)
Prediction of clinical drug response (CDR) of cancer patients, based on their clinical and molecular profiles obtained prior to administration of the drug, can play a significant role in individualized medicine. Machine learning models have the poten
Externí odkaz:
https://doaj.org/article/f5f68c2ab426446b9220523402df8df4