Literature DB >> 31548714

Setting the standards for machine learning in biology.

David T Jones1,2.   

Abstract

Mesh：

Year:  2019        PMID： 31548714     DOI： 10.1038/s41580-019-0176-5

Source DB:  PubMed          Journal:  Nat Rev Mol Cell Biol        ISSN： 1471-0072            Impact factor:   94.444


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  21 in total

1.  DOME: recommendations for supervised machine learning validation in biology.

Authors:  Ian Walsh; Dmytro Fishman; Dario Garcia-Gasulla; Tiina Titma; Gianluca Pollastri; Jennifer Harrow; Fotis E Psomopoulos; Silvio C E Tosatto
Journal:  Nat Methods       Date:  2021-07-27       Impact factor: 28.547

Review 2.  A guide to machine learning for biologists.

Authors:  Joe G Greener; Shaun M Kandathil; Lewis Moffat; David T Jones
Journal:  Nat Rev Mol Cell Biol       Date:  2021-09-13       Impact factor: 94.444

3.  Constructing benchmark test sets for biological sequence analysis using independent set algorithms.

Authors:  Samantha Petti; Sean R Eddy
Journal:  PLoS Comput Biol       Date:  2022-03-07       Impact factor: 4.475

Review 4.  Organ-On-A-Chip Models of the Blood-Brain Barrier: Recent Advances and Future Prospects.

Authors:  Satoru Kawakita; Kalpana Mandal; Lei Mou; Marvin Magan Mecwan; Yangzhi Zhu; Shaopei Li; Saurabh Sharma; Ana Lopez Hernandez; Huu Tuan Nguyen; Surjendu Maity; Natan Roberto de Barros; Aya Nakayama; Praveen Bandaru; Samad Ahadian; Han-Jun Kim; Rondinelli Donizetti Herculano; Eggehard Holler; Vadim Jucaud; Mehmet Remzi Dokmeci; Ali Khademhosseini
Journal:  Small       Date:  2022-08-17       Impact factor: 15.153

5.  An approachable, flexible and practical machine learning workshop for biologists.

Authors:  Chris S Magnano; Fangzhou Mu; Rosemary S Russ; Milica Cvetkovic; Debora Treu; Anthony Gitter
Journal:  Bioinformatics       Date:  2022-06-24       Impact factor: 6.931

6.  SidechainNet: An all-atom protein structure dataset for machine learning.

Authors:  Jonathan Edward King; David Ryan Koes
Journal:  Proteins       Date:  2021-07-12

Review 7.  Artificial Intelligence in Bulk and Single-Cell RNA-Sequencing Data to Foster Precision Oncology.

Authors:  Marco Del Giudice; Serena Peirone; Sarah Perrone; Francesca Priante; Fabiola Varese; Elisa Tirtei; Franca Fagioli; Matteo Cereda
Journal:  Int J Mol Sci       Date:  2021-04-27       Impact factor: 5.923

8.  Deep learning approach for quantification of organelles and misfolded polypeptide delivery within degradative compartments.

Authors:  Diego Morone; Alessandro Marazza; Timothy J Bergmann; Maurizio Molinari
Journal:  Mol Biol Cell       Date:  2020-05-13       Impact factor: 4.138

Review 9.  Big Data in Medicine, the Present and Hopefully the Future.

Authors:  Michela Riba; Cinzia Sala; Daniela Toniolo; Giovanni Tonon
Journal:  Front Med (Lausanne)       Date:  2019-11-15

10.  Interpretable deep learning uncovers cellular properties in label-free live cell images that are predictive of highly metastatic melanoma.

Authors:  Assaf Zaritsky; Andrew R Jamieson; Erik S Welf; Andres Nevarez; Justin Cillay; Ugur Eskiocak; Brandi L Cantarel; Gaudenz Danuser
Journal:  Cell Syst       Date:  2021-06-01       Impact factor: 11.091
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