Vivek Jayaswal
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Assessment of network module identification across complex diseases
S Choobdar, ME Ahsen, J Crawford, M Tomasoni, T Fang, D Lamparter, ...
Nature methods 16 (9), 843-852, 2019
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
MicroRNA-155 as an inducer of apoptosis and cell differentiation in Acute Myeloid Leukaemia
CA Palma, D Al Sheikha, TK Lim, A Bryant, TT Vu, V Jayaswal, DDF Ma
Molecular cancer 13 (1), 1-15, 2014
miR-10a is aberrantly overexpressed in Nucleophosmin1 mutated acute myeloid leukaemia and its suppression induces cell death
A Bryant, CA Palma, V Jayaswal, YW Yang, M Lutherborrow, DDF Ma
Molecular cancer 11, 1-9, 2012
Estimation of phylogeny using a general Markov model
V Jayaswal, LS Jermiin, J Robinson
Evolutionary Bioinformatics 1, 117693430500100005, 2005
Identification of microRNA-mRNA modules using microarray data
V Jayaswal, M Lutherborrow, DDF Ma, YH Yang
BMC genomics 12, 1-13, 2011
MicroRNA and mRNA expression profiling in metastatic melanoma reveal associations with BRAF mutation and patient prognosis
V Tembe, SJ Schramm, MS Stark, E Patrick, V Jayaswal, YH Tang, ...
Pigment cell & melanoma research 28 (3), 254-266, 2015
Mixture models of nucleotide sequence evolution that account for heterogeneity in the substitution process across sites and across lineages
V Jayaswal, TKF Wong, J Robinson, L Poladian, LS Jermiin
Systematic Biology 63 (5), 726-742, 2014
Phylogenetic model evaluation
LS Jermiin, V Jayaswal, F Ababneh, J Robinson
Bioinformatics: Data, Sequence Analysis and Evolution, 331-364, 2008
Expression profiling of cytogenetically normal acute myeloid leukemia identifies microRNAs that target genes involved in monocytic differentiation
M Lutherborrow, A Bryant, V Jayaswal, D Agapiou, C Palma, YH Yang, ...
American journal of hematology 86 (1), 2-11, 2011
Fluid intake and all-cause mortality, cardiovascular mortality and kidney function: a population-based longitudinal cohort study
SC Palmer, G Wong, S Iff, J Yang, V Jayaswal, JC Craig, E Rochtchina, ...
Nephrology Dialysis Transplantation 29 (7), 1377-1384, 2014
Estimation of phylogeny and invariant sites under the general Markov model of nucleotide sequence evolution
V Jayaswal, J Robinson, L Jermiin
Systematic biology 56 (2), 155-162, 2007
Identification of microRNAs with regulatory potential using a matched microRNA-mRNA time-course data
V Jayaswal, M Lutherborrow, DDF Ma, Y Hwa Yang
Nucleic acids research 37 (8), e60-e60, 2009
Two stationary nonhomogeneous Markov models of nucleotide sequence evolution
V Jayaswal, LS Jermiin, L Poladian, J Robinson
Systematic Biology 60 (1), 74-86, 2011
Knowledge-based analysis for detecting key signaling events from time-series phosphoproteomics data
P Yang, X Zheng, V Jayaswal, G Hu, JYH Yang, R Jothi
PLoS computational biology 11 (8), e1004403, 2015
Reducing model complexity of the general Markov model of evolution
V Jayaswal, F Ababneh, LS Jermiin, J Robinson
Molecular biology and evolution 28 (11), 3045-3059, 2011
Identifying optimal models of evolution
LS Jermiin, V Jayaswal, FM Ababneh, J Robinson
Bioinformatics: Volume I: Data, Sequence Analysis, and Evolution, 379-420, 2017
Nonadaptive molecular evolution of seminal fluid proteins in Drosophila
B Patlar, V Jayaswal, JM Ranz, A Civetta
Evolution 75 (8), 2102-2113, 2021
Community assessment of the predictability of cancer protein and phosphoprotein levels from genomics and transcriptomics
M Yang, F Petralia, Z Li, H Li, W Ma, X Song, S Kim, H Lee, H Yu, B Lee, ...
Cell systems 11 (2), 186-195. e9, 2020
SeqVis: a tool for detecting compositional heterogeneity among aligned nucleotide sequences
LS Jermiin, JWK Ho, KW Lau, V Jayaswal
Bioinformatics for DNA sequence analysis, 65-91, 2009
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