Click a folder for that year’s publications
M Li, J Shin, RD Risgaard, MJ Parries, J Wang, D Chasman, S Liu, S Roy, …
Genome Research 30 (3), 361-374
Evolution of regulatory networks associated with traits under selection in cichlids
TK Mehta, C Koch, W Nash, SA Knaack, P Sudhakar, M Olbei, …
bioRxiv, 496034
S Zhang, D Chasman, S Knaack, S Roy
Nature Communications 10 (1), 1-18
Imputed gene associations identify replicable trans‐acting genes enriched in transcription pathways and complex traits
HE Wheeler, S Ploch, AN Barbeira, R Bonazzola, A Andaleon, …
Genetic epidemiology 43 (6), 596-608
Defining Reprogramming Checkpoints from Single-Cell Analyses of Induced Pluripotency
KA Tran, SJ Pietrzak, NZ Zaidan, AF Siahpirani, SG McCalla, AS Zhou, …
Cell reports 27 (6), 1726-1741. e5
The cancer-associated genetic variant rs3903072 modulates immune cells in the tumor microenvironment
Y Zhang, M Manjunath, J Yan, BA Baur, S Zhang, S Roy, JS Song
Frontiers in Genetics 10, 754
Integrative Approaches for Inference of Genome-Scale Gene Regulatory Networks
AF Siahpirani, D Chasman, S Roy
Gene Regulatory Networks, 161-194
Y Zhang, M Manjunath, S Zhang, D Chasman, S Roy, JS Song
Cancer Research 78 (13 Supplement), 1220-1220
Integrative genomic analysis predicts causative cis-regulatory mechanisms of the breast cancer–associated genetic variant rs4415084
Y Zhang, M Manjunath, S Zhang, D Chasman, S Roy, JS Song
Cancer research 78 (7), 1579-1591
Can cancer GWAS variants modulate immune cells in the tumor microenvironment?
Y Zhang, M Manjunath, J Yan, BA Baur, S Zhang, S Roy, JS Song
bioRxiv, 493171
Evolution of regulatory networks controlling adaptive traits in cichlids
TK Mehta, C Koch, W Nash, SA Knaack, P Sudhakar, M Olbei, …
BioRxiv, 496034
Chromatin module inference on cellular trajectories identifies key transition points and poised epigenetic states in diverse developmental processes
S Roy, R Sridharan
Genome research 27 (7), 1250-1262
Inference and evolutionary analysis of genome-scale regulatory networks in large phylogenies
C Koch, J Konieczka, T Delorey, A Lyons, A Socha, K Davis, SA Knaack, …
Cell systems 4 (5), 543-558. e8
Physiological responses and gene co-expression network of mycorrhizal roots under K+ deprivation
K Garcia, D Chasman, S Roy, JM Ané
Plant physiology 173 (3), 1811-1823
AF Siahpirani, F Ay, S Roy
Genome biology 17 (1), 114
A proteomic atlas of the legume Medicago truncatula and its nitrogen-fixing endosymbiont Sinorhizobium meliloti
H Marx, CE Minogue, D Jayaraman, AL Richards, NW Kwiecien, …
Nature biotechnology 34 (11), 1198
A prior-based integrative framework for functional transcriptional regulatory network inference
AF Siahpirani, S Roy
Nucleic acids research 45 (4), e21-e21
Integrating transcriptomic and proteomic data using predictive regulatory network models of host response to pathogens
D Chasman, KB Walters, TJS Lopes, AJ Eisfeld, Y Kawaoka, S Roy
PLoS computational biology 12 (7), e1005013
Network-based approaches for analysis of complex biological systems
D Chasman, AF Siahpirani, S Roy
Current opinion in biotechnology 39, 157-166
A predictive modeling approach for cell line-specific long-range regulatory interactions
S Roy, AF Siahpirani, D Chasman, S Knaack, F Ay, R Stewart, M Wilson, …
Nucleic acids research 44 (4), 1977
Multi-task consensus clustering of genome-wide transcriptomes from related biological conditions
Z Niu, D Chasman, AJ Eisfeld, Y Kawaoka, S Roy
Bioinformatics 32 (10), 1509-1517
Reconstruction and analysis of the evolution of modular transcriptional regulatory programs using Arboretum
SA Knaack, DA Thompson, S Roy
Yeast Functional Genomics, 375-389
D Thompson, A Regev, S Roy
Annual review of cell and developmental biology 31, 399-428
A predictive modeling approach for cell line-specific long-range regulatory interactions
S Roy, AF Siahpirani, D Chasman, S Knaack, F Ay, R Stewart, M Wilson, …
Nucleic acids research 43 (18), 8694-8712
Deep sequencing of the Medicago truncatula root transcriptome reveals a massive and early interaction between nodulation factor and ethylene signals
E Larrainzar, BK Riely, SC Kim, N Carrasquilla-Garcia, HJ Yu, HJ Hwang, …
Plant Physiology 169 (1), 233-265
SIRT3 mediates multi-tissue coupling for metabolic fuel switching
KE Dittenhafer-Reed, AL Richards, J Fan, MJ Smallegan, AF Siahpirani, …
Cell metabolism 21 (4), 637-646
Collaborative rewiring of the pluripotency network by chromatin and signalling modulating pathways
KA Tran, SA Jackson, ZPG Olufs, NZ Zaidan, N Leng, C Kendziorski, …
Nature communications 6 (1), 1-14
SM Plis, J Sui, T Lane, S Roy, VP Clark, VK Potluru, RJ Huster, A Michael, …
Neuroimage 102, 35-48
A pan-cancer modular regulatory network analysis to identify common and cancer-specific network components
SA Knaack, AF Siahpirani, S Roy
Cancer informatics 13, CIN. S14058
S Roy, S Lagree, Z Hou, JA Thomson, R Stewart, AP Gasch
PLoS computational biology 9 (10)
Correction: Evolutionary principles of modular gene regulation in yeasts
DA Thompson, S Roy, M Chan, MP Styczynski, J Pfiffner, C French, …
Elife 2, e01114
Evolutionary principles of modular gene regulation in yeasts
DA Thompson, S Roy, M Chan, MP Styczynsky, J Pfiffner, C French, …
Elife 2, e00603
Arboretum: reconstruction and analysis of the evolutionary history of condition-specific transcriptional modules
S Roy, I Wapinski, J Pfiffner, C French, A Socha, J Konieczka, N Habib, …
Genome research 23 (6), 1039-1050
Calorie restriction and SIRT3 trigger global reprogramming of the mitochondrial protein acetylome
AS Hebert, KE Dittenhafer-Reed, W Yu, DJ Bailey, ES Selen, …
Molecular cell 49 (1), 186-199
S Roy, R Atlas
6.047/6.878 Lecture 18 Regulatory Networks: Inference, Analysis, Application
S Roy, S Feizi
Predictive regulatory models in Drosophila melanogaster by integrative inference of transcriptional networks
D Marbach, S Roy, F Ay, PE Meyer, R Candeias, T Kahveci, CA Bristow, …
Genome research 22 (7), 1334-1349
Predictive Regulatory Models in of Transcriptional Networks
D Marbach, S Roy, F Ay, PE Meyer, R Candeias, T Kahveci, CA Bristow, …
Cold Spring Harbor Laboratory Press
N Rhind, Z Chen, M Yassour, DA Thompson, BJ Haas, N Habib, …
Science 332 (6032), 930-936
A multiple network learning approach to capture system-wide condition-specific responses
S Roy, M Werner-Washburne, T Lane
Bioinformatics 27 (13), 1832-1838
The proteomics of quiescent and nonquiescent cell differentiation in yeast stationary-phase cultures
GS Davidson, RM Joe, S Roy, O Meirelles, CP Allen, MR Wilson, …
Molecular biology of the cell 22 (7), 988-998
Aging and the survival of quiescent and non-quiescent cells in yeast stationary-phase cultures
M Werner-Washburne, S Roy, GS Davidson
Aging research in yeast, 123-143
S Roy, J Ernst, PV Kharchenko, P Kheradpour, N Negre, ML Eaton, …
Science 330 (6012), 1787-1797
Information-Theoretic Inference of Gene Networks Using Backward Elimination.
P Meyer, D Marbach, S Roy, M Kellis
BioComp, 700-705
S Roy, S Plis, M Werner-Washburne, T Lane
IET systems biology 3 (5), 404-413
Learning structurally consistent undirected probabilistic graphical models
S Roy, T Lane, M Werner-Washburne
Proceedings of the 26th annual international conference on machine learning …
Exploiting amino acid composition for predicting protein-protein interactions
S Roy, D Martinez, H Platero, T Lane, M Werner-Washburne
PloS one 4 (11)
Inference of functional networks of condition-specific response-a case study of quiescence in yeast
S Roy, T Lane, M Werner-Washburne, D Martinez
Biocomputing 2009, 51-62
S Roy, M Werner-Washburne, T Lane
Bioinformatics 24 (10), 1318-1320
Characterization of differentiated quiescent and nonquiescent cells in yeast stationary-phase cultures
AD Aragon, AL Rodriguez, O Meirelles, S Roy, GS Davidson, PH Tapia, …
Molecular biology of the cell 19 (3), 1271-1280
P Kheradpour, A Stark, S Roy, M Kellis
Genome research 17 (12), 1919-1931
Discovery of functional elements in 12 Drosophila genomes using evolutionary signatures
A Stark, MF Lin, P Kheradpour, JS Pedersen, L Parts, JW Carlson, …
Nature 450 (7167), 219
Integrative Construction and Analysis of Condition-specific Biological Networks.
S Roy, T Lane, M Werner-Washburne
Proceedings of the National Conference on Artificial Intelligence 22 (2), 1898
A simulation framework for modeling combinatorial control in transcription regulatory networks
S Roy, T Lane, M Werner-Washburne
UNM Computer Science Technical Report, TR-CS-2007-06, 1-10
PD Wentzell, TK Karakach, S Roy, MJ Martinez, CP Allen, …
BMC bioinformatics 7 (1), 343
A hidden-state Markov model for cell population deconvolution
S Roy, T Lane, C Allen, AD Aragon, M Werner-Washburne
Journal of Computational Biology 13 (10), 1749-1774
Release of extraction-resistant mRNA in stationary phase Saccharomyces cerevisiae produces a massive increase in transcript abundance in response to stress
AD Aragon, GA Quiñones, EV Thomas, S Roy, M Werner-Washburne
Genome biology 7 (2), R9
S Roy, T Lane, M Werner-Washburne
Proceedings of the 5th international workshop on Bioinformatics, 46-53
Technical Reports
S. Roy, T. Lane, M. Werner-Washburne (2008). Learning structurally consistent undirected probabilistic graphical models. UNM Computer Science Technical Report, TR-CS-2008-14.
S. Roy, T. Lane, M. Werner-Washburne (2007). A Simulation Framework for Modeling Combinatorial Control in Transcription Regulatory Networks. UNM Computer Science Technical Report, TR-CS-2007-06.
S. Roy, T. Lane, C. Allen, A. D. Aragon, M. Werner-Washburne (2004). A Sequential Monte Carlo Sampling Approach for Cell Population Deconvolution from Microarray Data.
Posters and Workshops
Re-constructing the structural and functional components of genome-wide regulatory networks. Talk at Cold Spring Harbour Laboratory meeting on Systems Biology: Networks meeting, 2011.
Inferring predictive regulatory networks in Drosophila melanogaster by large-scale data integration. Poster presentation at the CSHL Biology of Genomes meeting, 2011.
S. Roy, C. A. Bristow, J. Konieczka, P. Kheradpour, A. Regev, M. Kellis. A Mixture of Experts model for predicting expression from sequence (2010). Intelligent Systems in Molecular Biology.
S. Roy, T. Lane, M. Werner-Washburne (2009). Learning condition-specific networks. Third Annual q-bio Conference on Cellular Information Processing. Santa Fe. New Mexico, USA.
S. Roy, S. Plis, M. Werner-Washburne (2008). Scalable learning of large networks. Second Annual q-bio Conference on Cellular Information Processing. Santa Fe. New Mexico, USA.
S. Roy, A. Stark, P. Kheradpour, M. Kellis, M. Werner-Washburne, T. Lane (2008). A relational framework for predicting tissues and links in the Drosophila regulatory network. Poster at RECOMB Satellite on Regulatory Genom ics and Systems Biology.
S. Roy, T. Lane, M. Werner-Washburne (2008). Integrative Construction and Analysis of Condition-specific Biological Network. Thirteenth AAAI Doctoral Consortium. Chicago. Illinois, USA
S. Roy, T. Lane, M. Werner-Washburne (2007). Intergative construction and analysis of condition-specific biological networks. AAAI Student Abstract and Poster Program. Vancouver, Canada.
S. Roy, T. Lane, M. Werner-Washburne (2006). Predicting protein-protein interactions using amino-acid composition. Second Annual RECOMB Satellite Workshop on Systems Biology. S.Roy, T. Lane, C. Allen, A. D. Aragon, M. Werner-Washburne (2006). Cell population deconvolution using particle filter. Poster presentation at the Tenth Annual International Conference on Research in Computational Molecular Biology (RECOMB).
S. Roy, T. Lane, C. Allen, A. D. Aragon, M. Werner-Washburne (2005). A Datamining approach to cell population deconvolution from gene expressions using particle filters. Fifth ACM SIGKDD Workshop on Data Mining in Bioinformatics.
Dissertation
Learning condition-specific networks (2009). UNM PhD Dissertation.
Master’s thesis
A Machine Learning Approach for Information Extraction (2005). UNM Master’s thesis.