Matthew Ruffalo
Matthew Ruffalo
Systems Scientist, Carnegie Mellon University
Verified email at - Homepage
Cited by
Cited by
Comparative analysis of algorithms for next-generation sequencing read alignment
M Ruffalo, T LaFramboise, M Koyutürk
Bioinformatics 27 (20), 2790-2796, 2011
Dynamics of clonal evolution in myelodysplastic syndromes
H Makishima, T Yoshizato, K Yoshida, MA Sekeres, T Radivoyevitch, ...
Nature genetics 49 (2), 204, 2017
Network-based integration of disparate omic data to identify" silent players" in cancer
M Ruffalo, M Koyutürk, R Sharan
PLoS computational biology 11 (12), e1004595, 2015
Accurate estimation of short read mapping quality for next-generation genome sequencing
M Ruffalo, M Koyutürk, S Ray, T LaFramboise
Bioinformatics 28 (18), i349-i355, 2012
A web server for comparative analysis of single-cell RNA-seq data
A Alavi, M Ruffalo, A Parvangada, Z Huang, Z Bar-Joseph
Nature communications 9 (1), 4768, 2018
Genome wide predictions of miRNA regulation by transcription factors
M Ruffalo, Z Bar-Joseph
Bioinformatics 32 (17), i746-i754, 2016
Whole-exome sequencing enhances prognostic classification of myeloid malignancies
M Ruffalo, H Husseinzadeh, H Makishima, B Przychodzen, M Ashkar, ...
Journal of biomedical informatics 58, 104-113, 2015
Reconstructing cancer drug response networks using multitask learning
M Ruffalo, P Stojanov, VK Pillutla, R Varma, Z Bar-Joseph
BMC systems biology 11 (1), 96, 2017
Construction of integrated microRNA and mRNA immune cell signatures to predict survival of patients with breast and ovarian cancer
M Ray, MM Ruffalo, Z Bar‐Joseph
Genes, Chromosomes and Cancer 58 (1), 34-42, 2019
In analogy to AML, MDS can be sub-classified by ancestral mutations
H Makishima, K Yoshida, T LaFramboise, BP Przychodzen, M Ruffalo, ...
Blood 124 (21), 823-823, 2014
Clinical “MUTATOME” Of Myelodysplastic Syndrome; Comparison To Primary Acute Myelogenous Leukemia
T LaFramboise, BP Przychodzen, K Yoshida, M Ruffalo, I Gómez-Seguí, ...
Blood 122 (21), 518-518, 2013
Protein interaction disruption in cancer
M Ruffalo, Z Bar-Joseph
BMC cancer 19 (1), 370, 2019
Network-guided prediction of aromatase inhibitor response in breast cancer
M Ruffalo, R Thomas, J Chen, AV Lee, S Oesterreich, Z Bar-Joseph
PLoS computational biology 15 (2), e1006730, 2019
Serial sequencing in myelodysplastic syndromes reveals dynamic changes in clonal architecture and allows for a new prognostic assessment of mutations detected in cross …
H Makishima, K Yoshida, T LaFramboise, T Yoshizato, M Ruffalo, ...
Blood 126 (23), 709-709, 2015
Whole exome sequencing to predict response to hypomethylating agents in MDS
HD Husseinzadeh, EP Evans, K Yoshida, H Makishima, A Jerez, ...
Blood 120 (21), 1698-1698, 2012
scQuery: a web server for comparative analysis of single-cell RNA-seq data
A Alavi, M Ruffalo, A Parvangada, Z Huang, Z Bar-Joseph
bioRxiv, 323238, 2018
Mutational Spectrum of Myelodysplastic Syndrome Malignancies Revealed by Whole Exome Sequencing
I Gómez-Seguí, BP Przychodzen, K Yoshida, M Ruffalo, A Jerez, ...
Blood 120 (21), 307-307, 2012
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