M
Meghana Chitale
Researcher at Purdue University
Publications - 18
Citations - 1339
Meghana Chitale is an academic researcher from Purdue University. The author has contributed to research in topics: Protein function prediction & Protein structure database. The author has an hindex of 12, co-authored 18 publications receiving 1188 citations.
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A large-scale evaluation of computational protein function prediction
Predrag Radivojac,Wyatt T. Clark,Tal Ronnen Oron,Alexandra M. Schnoes,Tobias Wittkop,Artem Sokolov,Artem Sokolov,Kiley Graim,Christopher S. Funk,Karin Verspoor,Asa Ben-Hur,Gaurav Pandey,Gaurav Pandey,Jeffrey M. Yunes,Ameet Talwalkar,Susanna Repo,Susanna Repo,Michael L Souza,Damiano Piovesan,Rita Casadio,Zheng Wang,Jianlin Cheng,Hai Fang,Julian Gough,Patrik Koskinen,Petri Törönen,Jussi Nokso-Koivisto,Liisa Holm,Domenico Cozzetto,Daniel W. A. Buchan,Kevin Bryson,David T. Jones,Bhakti Limaye,Harshal Inamdar,Avik Datta,Sunitha K Manjari,Rajendra Joshi,Meghana Chitale,Daisuke Kihara,Andreas Martin Lisewski,Serkan Erdin,Eric Venner,Olivier Lichtarge,Robert Rentzsch,Haixuan Yang,Alfonso E. Romero,Prajwal Bhat,Alberto Paccanaro,Tobias Hamp,Rebecca Kaßner,Stefan Seemayer,Esmeralda Vicedo,Christian Schaefer,Dominik Achten,Florian Auer,Ariane Boehm,Tatjana Braun,Maximilian Hecht,Mark Heron,Peter Hönigschmid,Thomas A. Hopf,Stefanie Kaufmann,Michael Kiening,Denis Krompass,Cedric Landerer,Yannick Mahlich,Manfred Roos,Jari Björne,Tapio Salakoski,Andrew Wong,Hagit Shatkay,Hagit Shatkay,Fanny Gatzmann,Ingolf Sommer,Mark N. Wass,Michael J.E. Sternberg,Nives Škunca,Fran Supek,Matko Bošnjak,Panče Panov,Sašo Džeroski,Tomislav Šmuc,Yiannis A. I. Kourmpetis,Yiannis A. I. Kourmpetis,Aalt D. J. van Dijk,Cajo J. F. ter Braak,Yuanpeng Zhou,Qingtian Gong,Xinran Dong,Weidong Tian,Marco Falda,Paolo Fontana,Enrico Lavezzo,Barbara Di Camillo,Stefano Toppo,Liang Lan,Nemanja Djuric,Yuhong Guo,Slobodan Vucetic,Amos Marc Bairoch,Amos Marc Bairoch,Michal Linial,Patricia C. Babbitt,Steven E. Brenner,Christine A. Orengo,Burkhard Rost,Sean D. Mooney,Iddo Friedberg +107 more
TL;DR: Today's best protein function prediction algorithms substantially outperform widely used first-generation methods, with large gains on all types of targets, and there is considerable need for improvement of currently available tools.
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PFP: Automated prediction of gene ontology functional annotations with confidence scores using protein sequence data
TL;DR: A benchmark comparison shows significant performance improvement of PFP relative to GOtcha, InterProScan, and PSI‐BLAST predictions, consistent with the performance of P FP as the overall best predictor in both the AFP‐SIG ′05 and CASP7 function assessments.
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ESG: extended similarity group method for automated protein function prediction
TL;DR: The extended similarity group (ESG) method, which performs iterative sequence database searches and annotates a query sequence with Gene Ontology terms, outperforms conventional PSI-BLAST and the protein function prediction (PFP) algorithm.
Journal ArticleDOI
Structure- and sequence-based function prediction for non-homologous proteins.
TL;DR: This work briefly reviews two avenues of computational function prediction methods, i.e. structure-based and sequence-based methods, which can effectively extract function information from distantly related proteins.
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New paradigm in protein function prediction for large scale omics analysis
TL;DR: Two recent approaches for function prediction which aim to provide large coverage in function prediction are focused on, namely omics data driven approaches and a thorough data mining approach on homology search results.