MicroRNA expression profiles and type 1 diabetes mellitus: systematic review and bioinformatic analysis TS Assmann, M Recamonde-Mendoza, BM De Souza, D Crispim Endocrine connections 6 (8), 773, 2017 | 129 | 2017 |
MicroRNAs and diabetic kidney disease: Systematic review and bioinformatic analysis TS Assmann, M Recamonde-Mendoza, BM de Souza, AC Bauer, ... Molecular and cellular endocrinology 477, 90-102, 2018 | 81 | 2018 |
What variables are important in predicting bovine viral diarrhea virus? A random forest approach G Machado, MR Mendoza, LG Corbellini Veterinary research 46, 1-15, 2015 | 76 | 2015 |
Identifying outbreaks of Porcine Epidemic Diarrhea virus through animal movements and spatial neighborhoods G Machado, C Vilalta, M Recamonde-Mendoza, C Corzo, M Torremorell, ... Scientific reports 9 (1), 1-12, 2019 | 57 | 2019 |
MicroRNA expression profile in plasma from type 1 diabetic patients: Case-control study and bioinformatic analysis TS Assmann, M Recamonde-Mendoza, M Punales, B Tschiedel, ... Diabetes research and clinical practice 141, 35-46, 2018 | 51 | 2018 |
Circulating miRNAs in diabetic kidney disease: case–control study and in silico analyses TS Assmann, M Recamonde-Mendoza, AR Costa, M Puñales, ... Acta diabetologica 56, 55-65, 2019 | 44 | 2019 |
RFMirTarget: predicting human microRNA target genes with a random forest classifier MR Mendoza, GC da Fonseca, G Loss-Morais, R Alves, R Margis, ... PloS one 8 (7), e70153, 2013 | 42 | 2013 |
Spectral alignment of networks S Feizi, G Quon, M Medard, M Kellis, A Jadbabaie | 33 | 2015 |
Spectral alignment of graphs S Feizi, G Quon, M Recamonde-Mendoza, M Medard, M Kellis, ... IEEE Transactions on Network Science and Engineering 7 (3), 1182-1197, 2019 | 31 | 2019 |
How to make more from exposure data? An integrated machine learning pipeline to predict pathogen exposure NM Fountain‐Jones, G Machado, S Carver, C Packer, ... Journal of Animal Ecology 88 (10), 1447-1461, 2019 | 28 | 2019 |
Circulating microRNAs in obese and lean heart failure patients: A case–control study with computational target prediction analysis JG Thome, MR Mendoza, AV Cheuiche, VL La Porta, D Silvello, ... Gene 574 (1), 1-10, 2015 | 28 | 2015 |
Detecting Aedes aegypti mosquitoes through audio classification with convolutional neural networks MS Fernandes, W Cordeiro, M Recamonde-Mendoza Computers in Biology and Medicine 129, 104152, 2021 | 21 | 2021 |
Urinary peptidomics and bioinformatics for the detection of diabetic kidney disease LA Brondani, AA Soares, M Recamonde-Mendoza, A Dall’Agnol, ... Scientific reports 10 (1), 1242, 2020 | 21 | 2020 |
Synergistic effects between ADORA2A and DRD2 genes on anxiety disorders in children with ADHD TT Fraporti, V Contini, L Tovo-Rodrigues, M Recamonde-Mendoza, ... Progress in Neuro-Psychopharmacology and Biological Psychiatry 93, 214-220, 2019 | 21 | 2019 |
Social choice in distributed classification tasks: Dealing with vertically partitioned data M Recamonde-Mendoza, ALC Bazzan Information Sciences 332, 56-71, 2016 | 16 | 2016 |
Reverse engineering of grns: An evolutionary approach based on the tsallis entropy MR Mendoza, FM Lopes, ALC Bazzan Proceedings of the 14th annual conference on Genetic and evolutionary …, 2012 | 15 | 2012 |
Evolving random boolean networks with genetic algorithms for regulatory networks reconstruction MR Mendoza, ALC Bazzan Proceedings of the 13th annual Conference on Genetic and Evolutionary …, 2011 | 14 | 2011 |
Spectral alignment of graphs S Feizi, G Quon, M Recamonde-Mendoza, M Medard, M Kellis, ... arXiv preprint arXiv:1602.04181, 2016 | 13 | 2016 |
TULP3: A potential biomarker in colorectal cancer? ITS Sartor, M Recamonde-Mendoza, P Ashton-Prolla PLoS One 14 (1), e0210762, 2019 | 12 | 2019 |
Calcium signaling alterations caused by epigenetic mechanisms in pancreatic cancer: from early markers to prognostic impact C Gregório, SC Soares-Lima, B Alemar, M Recamonde-Mendoza, ... Cancers 12 (7), 1735, 2020 | 11 | 2020 |