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Ney Lemke

Showing results (1-10 of 35) with videos related to

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BMC Bioinformatics|September 18, 2009
Towards the prediction of essential genes by integration of network topology, cellular localization and biological process informationMarcio L Acencio, Ney Lemke
Plos One|December 30, 2011
Using amino acid correlation and community detection algorithms to identify functional determinants in protein familiesLucas Bleicher, Ney Lemke, Richard Charles Garratt
Frontiers in Physiology|December 17, 2016
Corrigendum: Predicting Essential Genes and Proteins Based on Machine Learning and Network Topological Features: A Comprehensive ReviewXue Zhang, Marcio L Acencio, Ney Lemke
Frontiers in Physiology|December 24, 2015
Prediction of Druggable Proteins Using Machine Learning and Systems Biology: A Mini-ReviewGaurav Kandoi, Marcio L Acencio, Ney Lemke
Frontiers in Physiology|March 26, 2016
Predicting Essential Genes and Proteins Based on Machine Learning and Network Topological Features: A Comprehensive ReviewXue Zhang, Marcio Luis Acencio, Ney Lemke
Journal of Theoretical Biology|December 25, 2019
Cooperative and sequence-dependent model for RNAP dynamics: Application to ribosomal gene transcriptionRafael Takahiro Nakajima, Pedro Rafael Costa, Ney Lemke
BMC Genomics|August 21, 2012
HTRIdb: an open-access database for experimentally verified human transcriptional regulation interactionsLuiz A Bovolenta, Marcio L Acencio, Ney Lemke
Plos One|February 26, 2013
Cooperative RNA polymerase molecules behavior on a stochastic sequence-dependent model for transcription elongationPedro Rafael Costa, Marcio Luis Acencio, Ney Lemke
BMC Genomics|January 8, 2011
A machine learning approach for genome-wide prediction of morbid and druggable human genes based on systems-level dataPedro R Costa, Marcio L Acencio, Ney Lemke
Scientific Reports|November 16, 2017
PLA<sub>2</sub>-like proteins myotoxic mechanism: a dynamic model descriptionRafael J Borges, Ney Lemke, Marcos R M Fontes
Pageof 4

Showing results (1-10 of 35) with videos related to

Sort By:
Pageof 4
BMC Bioinformatics|September 18, 2009
Towards the prediction of essential genes by integration of network topology, cellular localization and biological process informationMarcio L Acencio, Ney Lemke
Plos One|December 30, 2011
Using amino acid correlation and community detection algorithms to identify functional determinants in protein familiesLucas Bleicher, Ney Lemke, Richard Charles Garratt
Frontiers in Physiology|December 17, 2016
Corrigendum: Predicting Essential Genes and Proteins Based on Machine Learning and Network Topological Features: A Comprehensive ReviewXue Zhang, Marcio L Acencio, Ney Lemke
Frontiers in Physiology|December 24, 2015
Prediction of Druggable Proteins Using Machine Learning and Systems Biology: A Mini-ReviewGaurav Kandoi, Marcio L Acencio, Ney Lemke
Frontiers in Physiology|March 26, 2016
Predicting Essential Genes and Proteins Based on Machine Learning and Network Topological Features: A Comprehensive ReviewXue Zhang, Marcio Luis Acencio, Ney Lemke
Journal of Theoretical Biology|December 25, 2019
Cooperative and sequence-dependent model for RNAP dynamics: Application to ribosomal gene transcriptionRafael Takahiro Nakajima, Pedro Rafael Costa, Ney Lemke
BMC Genomics|August 21, 2012
HTRIdb: an open-access database for experimentally verified human transcriptional regulation interactionsLuiz A Bovolenta, Marcio L Acencio, Ney Lemke
Plos One|February 26, 2013
Cooperative RNA polymerase molecules behavior on a stochastic sequence-dependent model for transcription elongationPedro Rafael Costa, Marcio Luis Acencio, Ney Lemke
BMC Genomics|January 8, 2011
A machine learning approach for genome-wide prediction of morbid and druggable human genes based on systems-level dataPedro R Costa, Marcio L Acencio, Ney Lemke
Scientific Reports|November 16, 2017
PLA<sub>2</sub>-like proteins myotoxic mechanism: a dynamic model descriptionRafael J Borges, Ney Lemke, Marcos R M Fontes
Pageof 4