Miguel Rocha

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	总计	2020 年至今
引用	7285	3560
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i10 指数	129	74

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Isabel RochaITQB NOVA - Universidade NOVA de Lisboa在 itqb.unl.pt 的电子邮件经过验证
Eugénio Campos FerreiraProfessor of Biological Engineering, Universidade do Minho在 deb.uminho.pt 的电子邮件经过验证
Paulo CortezFull Professor, ALGORITMI, Department Information Systems, University of Minho在 dsi.uminho.pt 的电子邮件经过验证
Jose Carlos Ferreira Maia NevesProfessor of Computer Science, The University of Minho在 di.uminho.pt 的电子邮件经过验证
Paulo MaiaSilicoLife SA在 silicolife.com 的电子邮件经过验证
Marcelo MaraschinUniversidade Federal de Santa Catarina在 ufsc.br 的电子邮件经过验证
Miguel RioProfessor of Computer Networks在 ucl.ac.uk 的电子邮件经过验证
Oscar DiasUniversity of Minho在 deb.uminho.pt 的电子邮件经过验证
Florentino Fdez-RiverolaProfessor, Computer Science Department, University of Vigo在 uvigo.es 的电子邮件经过验证
Rui MendesAlgoritmi, DI, Universidade do Minho在 di.uminho.pt 的电子邮件经过验证
Virgilio Gavicho UarrotaUniversidad de O´Higgins在 uoh.cl 的电子邮件经过验证
Kiran Raosaheb PatilMRC Toxicology Unit, University of Cambridge在 cam.ac.uk 的电子邮件经过验证
José P. FariaAssistant Computational Biologist在 anl.gov 的电子邮件经过验证
Julio Saez RodriguezHeidelberg University在 uni-heidelberg.de 的电子邮件经过验证
Bruno M. CostaLife and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho在 med.uminho.pt 的电子邮件经过验证
Christopher HenryComputational Biologist, Argonne National Laboratory在 mcs.anl.gov 的电子邮件经过验证
Daniel MachadoNorwegian University of Science and Technology在 ntnu.no 的电子邮件经过验证
Jens NielsenProfessor in Systems Biology, Chalmers University of Technology, Sweden在 chalmers.se 的电子邮件经过验证
Adam Paul ArkinDepartment of Bioengineering, University of California, Berkeley, Physical Biosciences Division, E.O在 lbl.gov 的电子邮件经过验证
Luis M. RochaGeorge J. Klir Professor of Systems Science and Industrial Engineering, Binghamton University (SUNY)在 binghamton.edu 的电子邮件经过验证

关注

Miguel Rocha

Associate Professor, Dept. Informatics and Centre Biological Engineering, Universidade do Minho

在 di.uminho.pt 的电子邮件经过验证

Bioinformatics Evolutionary Computation Systems Biology Machine Learning Neural Networks


标题按引用次数排序按年份排序按标题排序	引用次数引用次数	年份
OptFlux: an open-source software platform for in silico metabolic engineering I Rocha, P Maia, P Evangelista, P Vilaça, S Soares, JP Pinto, J Nielsen, ... BMC systems biology 4, 1-12, 2010	497	2010
Particle swarms for feedforward neural network training R Mendes, P Cortez, M Rocha, J Neves Proceedings of the 2002 International Joint Conference on Neural Networks …, 2002	429	2002
Community assessment to advance computational prediction of cancer drug combinations in a pharmacogenomic screen MP Menden, D Wang, MJ Mason, B Szalai, KC Bulusu, Y Guan, T Yu, ... Nature communications 10 (1), 2674, 2019	325	2019
Multi‐scale Internet traffic forecasting using neural networks and time series methods P Cortez, M Rio, M Rocha, P Sousa Expert Systems 29 (2), 143-155, 2012	261	2012
Modeling formalisms in systems biology D Machado, RS Costa, M Rocha, EC Ferreira, B Tidor, I Rocha AMB express 1, 1-14, 2011	250	2011
Deep learning for drug response prediction in cancer D Baptista, PG Ferreira, M Rocha Briefings in bioinformatics 22 (1), 360-379, 2021	205	2021
Reconstructing genome-scale metabolic models with merlin O Dias, M Rocha, EC Ferreira, I Rocha Nucleic acids research 43 (8), 3899-3910, 2015	185	2015
Internet traffic forecasting using neural networks P Cortez, M Rio, M Rocha, P Sousa The 2006 IEEE international joint conference on neural network proceedings …, 2006	182	2006
Prediction of overall survival for patients with metastatic castration-resistant prostate cancer: development of a prognostic model through a crowdsourced challenge with open … J Guinney, T Wang, TD Laajala, KK Winner, JC Bare, EC Neto, SA Khan, ... The Lancet Oncology 18 (1), 132-142, 2017	169	2017
Metabolomics combined with chemometric tools (PCA, HCA, PLS-DA and SVM) for screening cassava (Manihot esculenta Crantz) roots during postharvest physiological deterioration VG Uarrota, R Moresco, B Coelho, E da Costa Nunes, LAM Peruch, ... Food Chemistry 161, 67-78, 2014	168	2014
Evolution of neural networks for classification and regression M Rocha, P Cortez, J Neves Neurocomputing 70 (16-18), 2809-2816, 2007	153	2007
Preventing premature convergence to local optima in genetic algorithms via random offspring generation M Rocha, J Neves Multiple Approaches to Intelligent Systems: 12th International Conference on …, 1999	149	1999
In Silico Constraint-Based Strain Optimization Methods: the Quest for Optimal Cell Factories P Maia, M Rocha, I Rocha Microbiology and Molecular Biology Reviews 80 (1), 45-67, 2016	143	2016
Generative deep learning for targeted compound design T Sousa, J Correia, V Pereira, M Rocha Journal of chemical information and modeling 61 (11), 5343-5361, 2021	140	2021
Causal integration of multi‐omics data with prior knowledge to generate mechanistic hypotheses A Dugourd, C Kuppe, M Sciacovelli, E Gjerga, A Gabor, KB Emdal, ... Molecular Systems Biology 17 (1), e9730, 2021	136	2021
Natural computation meta-heuristics for the in silico optimization of microbial strains M Rocha, P Maia, R Mendes, JP Pinto, EC Ferreira, J Nielsen, KR Patil, ... BMC bioinformatics 9, 1-16, 2008	131	2008
Evolving time series forecasting ARMA models P Cortez, M Rocha, J Neves Journal of Heuristics 10, 415-429, 2004	124	2004
Bridging the layers: towards integration of signal transduction, regulation and metabolism into mathematical models E Gonçalves, J Bucher, A Ryll, J Niklas, K Mauch, S Klamt, M Rocha, ... Molecular BioSystems 9 (7), 1576-1583, 2013	120	2013
Transcript level and sequence determinants of protein abundance and noise in Escherichia coli JC Guimaraes, M Rocha, AP Arkin Nucleic acids research 42 (8), 4791-4799, 2014	115	2014
A review of dynamic modeling approaches and their application in computational strain optimization for metabolic engineering OD Kim, M Rocha, P Maia Frontiers in microbiology 9, 1690, 2018	99	2018

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