Literature DB >> 29906441

Visible Machine Learning for Biomedicine.

Michael K Yu1, Jianzhu Ma2, Jasmin Fisher3, Jason F Kreisberg2, Benjamin J Raphael4, Trey Ideker5.   

Abstract

A major ambition of artificial intelligence lies in translating patient data to successful therapies. Machine learning models face particular challenges in biomedicine, however, including handling of extreme data heterogeneity and lack of mechanistic insight into predictions. Here, we argue for "visible" approaches that guide model structure with experimental biology.
Copyright © 2018. Published by Elsevier Inc.

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Year:  2018        PMID： 29906441      PMCID： PMC6483071          DOI： 10.1016/j.cell.2018.05.056

Source DB:  PubMed          Journal:  Cell        ISSN： 0092-8674            Impact factor:   41.582


  12 in total

Review 1.  Executable cell biology.

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Review 2.  Deep learning.

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3.  A whole-cell computational model predicts phenotype from genotype.

Authors:  Jonathan R Karr; Jayodita C Sanghvi; Derek N Macklin; Miriam V Gutschow; Jared M Jacobs; Benjamin Bolival; Nacyra Assad-Garcia; John I Glass; Markus W Covert
Journal:  Cell       Date:  2012-07-20       Impact factor: 41.582

Review 4.  An Expanded View of Complex Traits: From Polygenic to Omnigenic.

Authors:  Evan A Boyle; Yang I Li; Jonathan K Pritchard
Journal:  Cell       Date:  2017-06-15       Impact factor: 41.582

Review 5.  Network analysis of GWAS data.

Authors:  Mark D M Leiserson; Jonathan V Eldridge; Sohini Ramachandran; Benjamin J Raphael
Journal:  Curr Opin Genet Dev       Date:  2013-11-26       Impact factor: 5.578

6.  Using neural networks for reducing the dimensions of single-cell RNA-Seq data.

Authors:  Chieh Lin; Siddhartha Jain; Hannah Kim; Ziv Bar-Joseph
Journal:  Nucleic Acids Res       Date:  2017-09-29       Impact factor: 16.971

7.  Functional characterization of somatic mutations in cancer using network-based inference of protein activity.

Authors:  Mariano J Alvarez; Yao Shen; Federico M Giorgi; Alexander Lachmann; B Belinda Ding; B Hilda Ye; Andrea Califano
Journal:  Nat Genet       Date:  2016-06-20       Impact factor: 38.330

8.  Using deep learning to model the hierarchical structure and function of a cell.

Authors:  Jianzhu Ma; Michael Ku Yu; Samson Fong; Keiichiro Ono; Eric Sage; Barry Demchak; Roded Sharan; Trey Ideker
Journal:  Nat Methods       Date:  2018-03-05       Impact factor: 28.547

9.  Network-based classification of breast cancer metastasis.

Authors:  Han-Yu Chuang; Eunjung Lee; Yu-Tsueng Liu; Doheon Lee; Trey Ideker
Journal:  Mol Syst Biol       Date:  2007-10-16       Impact factor: 11.429

Review 10.  Machine learning applications in cancer prognosis and prediction.

Authors:  Konstantina Kourou; Themis P Exarchos; Konstantinos P Exarchos; Michalis V Karamouzis; Dimitrios I Fotiadis
Journal:  Comput Struct Biotechnol J       Date:  2014-11-15       Impact factor: 7.271
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  28 in total

Review 1.  Systems Biology of Cancer Metastasis.

Authors:  Yasir Suhail; Margo P Cain; Kiran Vanaja; Paul A Kurywchak; Andre Levchenko; Raghu Kalluri
Journal:  Cell Syst       Date:  2019-08-28       Impact factor: 10.304

2.  Transcriptional trajectories of human kidney injury progression.

Authors:  Pietro E Cippà; Bo Sun; Jing Liu; Liang Chen; Maarten Naesens; Andrew P McMahon
Journal:  JCI Insight       Date:  2018-11-15

Review 3.  Molecular networks in Network Medicine: Development and applications.

Authors:  Edwin K Silverman; Harald H H W Schmidt; Eleni Anastasiadou; Lucia Altucci; Marco Angelini; Lina Badimon; Jean-Luc Balligand; Giuditta Benincasa; Giovambattista Capasso; Federica Conte; Antonella Di Costanzo; Lorenzo Farina; Giulia Fiscon; Laurent Gatto; Michele Gentili; Joseph Loscalzo; Cinzia Marchese; Claudio Napoli; Paola Paci; Manuela Petti; John Quackenbush; Paolo Tieri; Davide Viggiano; Gemma Vilahur; Kimberly Glass; Jan Baumbach
Journal:  Wiley Interdiscip Rev Syst Biol Med       Date:  2020-04-19

4.  A White-Box Machine Learning Approach for Revealing Antibiotic Mechanisms of Action.

Authors:  Jason H Yang; Sarah N Wright; Meagan Hamblin; Douglas McCloskey; Miguel A Alcantar; Lars Schrübbers; Allison J Lopatkin; Sangeeta Satish; Amir Nili; Bernhard O Palsson; Graham C Walker; James J Collins
Journal:  Cell       Date:  2019-05-09       Impact factor: 41.582

5.  A scalable, open-source implementation of a large-scale mechanistic model for single cell proliferation and death signaling.

Authors:  Cemal Erdem; Arnab Mutsuddy; Ethan M Bensman; William B Dodd; Michael M Saint-Antoine; Mehdi Bouhaddou; Robert C Blake; Sean M Gross; Laura M Heiser; F Alex Feltus; Marc R Birtwistle
Journal:  Nat Commun       Date:  2022-06-21       Impact factor: 17.694

Review 6.  Harnessing the Power of Artificial Intelligence in Otolaryngology and the Communication Sciences.

Authors:  Blake S Wilson; Debara L Tucci; David A Moses; Edward F Chang; Nancy M Young; Fan-Gang Zeng; Nicholas A Lesica; Andrés M Bur; Hannah Kavookjian; Caroline Mussatto; Joseph Penn; Sara Goodwin; Shannon Kraft; Guanghui Wang; Jonathan M Cohen; Geoffrey S Ginsburg; Geraldine Dawson; Howard W Francis
Journal:  J Assoc Res Otolaryngol       Date:  2022-04-20

7.  Predicting Drug Response and Synergy Using a Deep Learning Model of Human Cancer Cells.

Authors:  Brent M Kuenzi; Jisoo Park; Samson H Fong; Kyle S Sanchez; John Lee; Jason F Kreisberg; Jianzhu Ma; Trey Ideker
Journal:  Cancer Cell       Date:  2020-10-22       Impact factor: 31.743

Review 8.  The social nature of mitochondria: Implications for human health.

Authors:  Martin Picard; Carmen Sandi
Journal:  Neurosci Biobehav Rev       Date:  2020-07-08       Impact factor: 8.989

Review 9.  Executable cancer models: successes and challenges.

Authors:  Matthew A Clarke; Jasmin Fisher
Journal:  Nat Rev Cancer       Date:  2020-04-27       Impact factor: 69.800

10.  Privacy-Preserving Artificial Intelligence Techniques in Biomedicine.

Authors:  Reihaneh Torkzadehmahani; Reza Nasirigerdeh; David B Blumenthal; Tim Kacprowski; Markus List; Julian Matschinske; Julian Spaeth; Nina Kerstin Wenke; Jan Baumbach
Journal:  Methods Inf Med       Date:  2022-01-21       Impact factor: 1.800
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