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Your search keyword '"Ammad-Ud-Din M"' showing total 2 results
Start Over Author "Ammad-Ud-Din M" Topic computational biology
2 results on '"Ammad-Ud-Din M"'

1. Systematic identification of feature combinations for predicting drug response with Bayesian multi-view multi-task linear regression.

Author

Ammad-Ud-Din M, Khan SA, Wennerberg K, and Aittokallio T

Subjects
Algorithms, Antineoplastic Agents pharmacology, Bayes Theorem, Humans, Linear Models, Neoplasms genetics, Neoplasms metabolism, Signal Transduction drug effects, Antineoplastic Agents therapeutic use, Computational Biology methods, Models, Biological, Neoplasms drug therapy, Precision Medicine methods, Software
Abstract

Motivation: A prime challenge in precision cancer medicine is to identify genomic and molecular features that are predictive of drug treatment responses in cancer cells. Although there are several computational models for accurate drug response prediction, these often lack the ability to infer which feature combinations are the most predictive, particularly for high-dimensional molecular datasets. As increasing amounts of diverse genome-wide data sources are becoming available, there is a need to build new computational models that can effectively combine these data sources and identify maximally predictive feature combinations., Results: We present a novel approach that leverages on systematic integration of data sources to identify response predictive features of multiple drugs. To solve the modeling task we implement a Bayesian linear regression method. To further improve the usefulness of the proposed model, we exploit the known human cancer kinome for identifying biologically relevant feature combinations. In case studies with a synthetic dataset and two publicly available cancer cell line datasets, we demonstrate the improved accuracy of our method compared to the widely used approaches in drug response analysis. As key examples, our model identifies meaningful combinations of features for the well known EGFR, ALK, PLK and PDGFR inhibitors., Availability and Implementation: The source code of the method is available at https://github.com/suleimank/mvlr ., Contact: muhammad.ammad-ud-din@helsinki.fi or suleiman.khan@helsinki.fi., Supplementary Information: Supplementary data are available at Bioinformatics online., (© The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com)

Published
2017
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2. Prediction of human population responses to toxic compounds by a collaborative competition

Author

Eduati, F, Mangravite, L, Wang, T, Tang, Hongxiang, Bare, J, Huang, R, Norman, T, Kellen, M, Menden, M, Yang, J, Zhan, X, Zhong, R, Xiao, G, Xia, M, Abdo, N, Kosyk, O, Friend, S, Stolovitzky, G, Dearry, A, Tice, R, Simeonov, S, Rusyn, I, Wright, F, Xie, Y, Alaimo, S, Amadoz, A, Ammad-ud-din, M, Chloé-Azencott, A, Bacardit, J, Barron, P, Bernard, E, Beyer, A, Bin, S, van Bömmel, A, Borgwardt, K, Brys, A, Caffrey, B, Chang, J, Christodoulou, E, Clément-Ziza, M, Cohen, T, Cowherd, M, Demeyer, S, Dopazo, J, Elhard, J, Falcao, A, Ferro, A, Friedenberg, D, Giugno, R, Gong, Y, Gorospe, J, Granville, C, Grimm, D, Heinig, M, Hernansaiz, R, Hochreiter, S, Liang-Huang, C, Huska, M, Jiao, Y, Klambauer, G, Kuhn, M, Kursa, M, Kutum, R, Lazzarini, N, Lee, I, Leung, M, K W, Lim, Liu, C, F L, López, Mammana, A, Mayr, A, Michoel, T, Mongiovì, M, Moore, J, Narasimhan, R, Opiyo, S, Pandey, G, Peabody, A, Perner, J, Pulvirenti, A, Rawlik, K, Reinhardt, S, Riffle, C, Ruderfer, D, Sander, A, Savage, R, Scornet, E, Sebastian-Leon, P, Sharan, R, Simon-Gabriel, C, Stoven, V, Sun, J, Tang, H, Teixeira, A, Tenesa, A, Jean-Vert, P, Vingron, M, Walter, T, Whalen, S, Wiśniewska, Z, Wu, Y, Xu, H, Zhang, S, Zhao, J, W Zheng J, Ziwei, D, Simeonov, A, Raymond, R Tice, Saez-Rodriguez, J., NIEHS-NCATS-UNC DREAM Toxicogenetics Collaboration, Institut de Recherche pour le Développement (IRD), National Center for Advancing Translational Sciences (NCATS), National Institutes of Health [Bethesda] (NIH), Data Storage Institute - A*STAR, Capital Normal University [Beijing], Southwest University of China, sans affiliation, Shanghai Ocean University, Centre de Bioinformatique (CBIO), MINES ParisTech - École nationale supérieure des mines de Paris-PSL Research University (PSL), Cancer et génôme: Bioinformatique, biostatistiques et épidémiologie d'un système complexe, MINES ParisTech - École nationale supérieure des mines de Paris-Institut Curie-Institut National de la Santé et de la Recherche Médicale (INSERM), Institut National de l'Information Géographique et Forestière [IGN] (IGN), Systèmes Productifs, Logistique, Organisation des Transports et Travail (IFSTTAR/AME/SPLOTT), Communauté Université Paris-Est-Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux (IFSTTAR), Biotechnology Center [Dresden] (BIOTEC), Technische Universität Dresden (TUD), Laboratoire National de Métrologie et d'Essais [Trappes] (LNE ), Centre for Biomedical Network Research on Rare Diseases (CIBERER), Department of Computational Genomics, Centro de Investigación Príncipe Felipe (CIPF), Functional Genomics Node (INB), CIPF, Computational Intelligence Research Group (CA3), Centre of Technology and Systems (CTS), Faculty of Sciences and Technology (FCT NOVA), Universidade Nova de Lisboa (NOVA)-Universidade Nova de Lisboa (NOVA)-Faculty of Sciences and Technology (FCT NOVA), Universidade Nova de Lisboa (NOVA)-Universidade Nova de Lisboa (NOVA)-Faculdade de Ciências e Tecnologia (FCT NOVA), Universidade Nova de Lisboa (NOVA), ACEEE, The Institute of Doctors Engineers and Scientists - IDES, Laboratoire Traitement et Communication de l'Information (LTCI), Télécom ParisTech-Institut Mines-Télécom [Paris] (IMT)-Centre National de la Recherche Scientifique (CNRS), Laboratory of Information, Network and Communication Sciences (LINCS), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut Mines-Télécom [Paris] (IMT), Institute of Computational Biology, Helmholtz-Zentrum München (HZM), Stony Brook University [SUNY] (SBU), State University of New York (SUNY), University of Pensylvania, Institute for Infocomm Research - I²R [Singapore], Institut de recherche en informatique de Toulouse (IRIT), Université Toulouse 1 Capitole (UT1)-Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées, Department of Mechanical and Aerospace Engineering [Davis], University of California [Davis] (UC Davis), University of California-University of California, Commonwealth Scientific and Industrial Research Organisation [Canberra] (CSIRO), Ludwig-Maximilians-Universität München (LMU), Laboratoire Architecture, Ville, Urbanisme, Environnement (LAVUE), École nationale supérieure d'architecture de Paris-La Villette (ENSAPLV)-École nationale supérieure d'architecture de Paris Val-de-Seine (ENSA PVDS)-Université Paris 8 Vincennes-Saint-Denis (UP8)-Ministère de la Culture (MC)-Université Paris Nanterre (UPN)-Centre National de la Recherche Scientifique (CNRS), Laboratoire de Statistique Théorique et Appliquée (LSTA), Université Pierre et Marie Curie - Paris 6 (UPMC), Agricultural Technological Extensive Station of Luntai County in Xinjiang, Medstar Research Institute, Huawei Technologies [Shanghaï], School of Economics and Business Administration (School of Economics and Business Administration), Beijing Normal University, National Center for Mathematics and Interdisciplinary Sciences [Beijing] (NCMIS), Academy of Mathematics and Systems Science (AMSS), Chinese Academy of Sciences [Beijing] (CAS)-Chinese Academy of Sciences [Beijing] (CAS), Division of Biostatistics, Helmholtz-Institute for Biomedical Engineering [RWTH Aachen University], European Bioinformatics Institute [Hinxton] (EMBL-EBI), EMBL Heidelberg, Agricultural Information Institute (AII), Chinese Academy of Agricultural Sciences (CAAS), Department of Computer Science - Lafayette College, Lafayette College [Easton], MINES ParisTech - École nationale supérieure des mines de Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL), Cancer et génome: Bioinformatique, biostatistiques et épidémiologie d'un système complexe, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut Curie [Paris]-Institut National de la Santé et de la Recherche Médicale (INSERM), Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux (IFSTTAR)-Communauté Université Paris-Est, Technische Universität Dresden = Dresden University of Technology (TU Dresden), Faculdade de Ciências e Tecnologia = School of Science & Technology (FCT NOVA), Universidade Nova de Lisboa = NOVA University Lisbon (NOVA)-Universidade Nova de Lisboa = NOVA University Lisbon (NOVA)-Faculdade de Ciências e Tecnologia = School of Science & Technology (FCT NOVA), Universidade Nova de Lisboa = NOVA University Lisbon (NOVA)-Universidade Nova de Lisboa = NOVA University Lisbon (NOVA), Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Paris 8 Vincennes-Saint-Denis (UP8)-École nationale supérieure d'architecture de Paris-La Villette (ENSAPLV)-Université Paris Nanterre (UPN)-École nationale supérieure d'architecture de Paris Val-de-Seine (ENSA PVDS)-Centre National de la Recherche Scientifique (CNRS)-Ministère de la Culture (MC), Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS), Beijing Normal University (BNU), Sans affiliation, Mines Paris - PSL (École nationale supérieure des mines de Paris), Helmholtz Zentrum München = German Research Center for Environmental Health, Université Fédérale Toulouse Midi-Pyrénées-Toulouse Mind & Brain Institut (TMBI), Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse III - Paul Sabatier (UT3), Department of Mechanical and Aerospace Engineering [Univ California Davis] (MAE - UC Davis), University of California (UC)-University of California (UC), Université Paris 8 Vincennes-Saint-Denis (UP8)-École nationale supérieure d'architecture de Paris-La Villette (ENSAPLV), HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-Université Paris Nanterre (UPN)-École nationale supérieure d'architecture de Paris Val-de-Seine (ENSA PVDS)-Centre National de la Recherche Scientifique (CNRS)-Ministère de la Culture (MC), Centre National de la Recherche Scientifique (CNRS)-Université Paris Nanterre (UPN)-Ministère de la Culture (MC)-Université Paris 8 Vincennes-Saint-Denis (UP8)-École nationale supérieure d'architecture de Paris Val-de-Seine (ENSA PVDS)-École nationale supérieure d'architecture de Paris-La Villette (ENSAPLV), Institut Mines-Télécom [Paris] (IMT)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université Pierre et Marie Curie - Paris 6 (UPMC), Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT)-Université de Toulouse (UT)-Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université de Toulouse (UT)-Toulouse Mind & Brain Institut (TMBI), Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT), and MINES ParisTech - École nationale supérieure des mines de Paris-Institut Curie [Paris]-Institut National de la Santé et de la Recherche Médicale (INSERM)

Subjects
Bioinformatics, MESH: Risk Assessment, Applied Microbiology and Biotechnology, MESH: Dose-Response Relationship, Drug, Genotype, MESH: Incidence, MESH: Models, Genetic, Cytotoxicity, ComputingMilieux_MISCELLANEOUS, media_common, education.field_of_study, High-throughput screening, MESH: Genetic Predisposition to Disease, drug, [SDV.BIBS]Life Sciences [q-bio]/Quantitative Methods [q-bio.QM], [INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV], Trait, Molecular Medicine, Health occupations, Predictive medicine, Risk factors, Risk assessment, Biotechnology, data mining, expression, MESH: High-Throughput Screening Assays, media_common.quotation_subject, Population, Biomedical Engineering, MESH: Genetics, Population, Bioengineering, Computational biology, Biology, Competition (biology), Article, MESH: Computer Simulation, ddc:570, 1000 Genomes Project, education, MESH: Toxicity Tests, ta113, MESH: Humans, [INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV], MESH: Hazardous Substances, MESH: Lymphocytes, [INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM], RA
Abstract

The ability to computationally predict the effects of toxic compounds on humans could help address the deficiencies of current chemical safety testing. Here, we report the results from a community-based DREAM challenge to predict toxicities of environmental compounds with potential adverse health effects for human populations. We measured the cytotoxicity of 156 compounds in 884 lymphoblastoid cell lines for which genotype and transcriptional data are available as part of the Tox21 1000 Genomes Project. The challenge participants developed algorithms to predict interindividual variability of toxic response from genomic profiles and population-level cytotoxicity data from structural attributes of the compounds. 179 submitted predictions were evaluated against an experimental data set to which participants were blinded. Individual cytotoxicity predictions were better than random, with modest correlations (Pearson's r < 0.28), consistent with complex trait genomic prediction. In contrast, predictions of population-level response to different compounds were higher (r < 0.66). The results highlight the possibility of predicting health risks associated with unknown compounds, although risk estimation accuracy remains suboptimal., Nature Biotechnology, 33 (9), ISSN:1546-1696, ISSN:1087-0156

Published
2015
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