| Multiplex methods provide effective integration of multi-omic data in genome-scale models C Angione, M Conway, P Lió BMC bioinformatics 17 (4), 257-269, 2016 | 54 | 2016 |
| Seeing the wood for the trees: a forest of methods for optimization and omic-network integration in metabolic modelling S Vijayakumar, M Conway, P Lió, C Angione Briefings in bioinformatics 19 (6), 1218-1235, 2018 | 47 | 2018 |
| Optimization of multi-omic genome-scale models: Methodologies, hands-on tutorial, and perspectives S Vijayakumar, M Conway, P Lió, C Angione Metabolic Network Reconstruction and Modeling: Methods and Protocols, 389-408, 2018 | 18 | 2018 |
| Transcriptome and proteome analysis of Salmonella enterica serovar Typhimurium systemic infection of wild type and immune-deficient mice O Oshota, M Conway, M Fookes, F Schreiber, RR Chaudhuri, L Yu, ... PloS one 12 (8), e0181365, 2017 | 10 | 2017 |
| Iterative multi level calibration of metabolic networks M Conway, C Angione, P Lio Current Bioinformatics 11 (1), 93-105, 2016 | 8 | 2016 |
| STAble: a novel approach to de novo assembly of RNA-seq data and its application in a metabolic model network based metatranscriptomic workflow I Saggese, E Bona, M Conway, F Favero, M Ladetto, P Liò, G Manzini, ... BMC bioinformatics 19, 127-137, 2018 | 6 | 2018 |
| CiliateGEM: an open-project and a tool for predictions of ciliate metabolic variations and experimental condition design A Mancini, F Eyassu, M Conway, A Occhipinti, P Liò, C Angione, ... BMC bioinformatics 19 (15), 123-130, 2018 | 3 | 2018 |
| Bioinformatics challenges and potentialities in studying extreme environments C Angione, P Lió, S Pucciarelli, B Can, M Conway, M Lotti, H Bokhari, ... Computational Intelligence Methods for Bioinformatics and Biostatistics …, 2016 | 1 | 2016 |
| Machine learning methods for detecting structure in metabolic flow networks MJ Conway University of Cambridge, 2020 | | 2020 |
| Machine learning methods for detecting structure in metabolic flow networks MJ Conway University of Cambridge, Computer Laboratory, 2020 | | 2020 |
