Ilya Shmulevich

发表

Abstract B051: Facilitating translational research with interactive tools for immuno-oncology data

Vesteinn Thorsson, James A. Eddy, Andrew Lamb, 2019 .

A framework for ordinal-based image correspondence

Moncef Gabbouj, Ilya Shmulevich, Bogdan Cramariuc, 2000, 2000 10th European Signal Processing Conference.

Adaptable data management for systems biology investigations

Ilya Shmulevich, John Boyle, Hector Rovira, 2009, BMC Bioinformatics.

Block-median pyramidal transform: analysis and denoising applications

Jaakko Astola, Karen O. Egiazarian, Ilya Shmulevich, 2001, IEEE Trans. Signal Process..

Stack Filters and Free Distributive Lattices

Thomas Sellke, Ilya Shmulevich, Moncef Gabbouj, 1995 .

Emergence of diversity in homogeneous coupled Boolean networks.

Ilya Shmulevich, Chris Kang, Boris Aguilar, 2018, Physical review. E.

Simcluster: clustering enumeration gene expression data on the simplex space

Ilya Shmulevich, Ricardo Z. N. Vêncio, Leonardo Varuzza, 2007, BMC Bioinformatics.

Noise in a small genetic circuit that undergoes bifurcation

Ping Ao, Ilya Shmulevich, Trent Toulouse, 2005, Complex..

Nonlinear modeling of protein expressions in protein arrays

Jaakko Astola, Ioan Tabus, Jorma Rissanen, 2006, IEEE Transactions on Signal Processing.

Microarray quality control

Jaakko Astola, Ilya Shmulevich, Wei Oct. Zhang, 2004 .

Probabilistic Boolean Networks - The Modeling and Control of Gene Regulatory Networks

Edward R. Dougherty, Ilya Shmulevich, E. Dougherty, 2010 .

ProbCD: enrichment analysis accounting for categorization uncertainty

Ilya Shmulevich, Ricardo Z. N. Vêncio, I. Shmulevich, 2007, BMC Bioinformatics.

Nonparametric density estimation with adaptive varying window size

Vladimir Katkovnik, Ilya Shmulevich, V. Katkovnik, 2001, SPIE Remote Sensing.

On Learning Gene Regulatory Networks Under the Boolean Network Model

Ilya Shmulevich, Olli Yli-Harja, Harri Lähdesmäki, 2003, Machine Learning.

Editorial

Kenneth E. Barner, Giovanni L. Sicuranza, Gonzalo R. Arce, 2001, EURASIP J. Adv. Signal Process..

Statistics of stack filters with mirrored threshold decomposition

Gonzalo R. Arce, Ilya Shmulevich, José L. Paredes, 2000, 2000 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.00CH37100).

Output Distributions of Stack Filters Using Ordered Binary Decision Diagrams

Karen O. Egiazarian, Ilya Shmulevich, Olli Yli-Harja, 2000 .

Genetic Regulatory Networks: A Nonlinear Signal Processing Perspective

Edward R. Dougherty, Ilya Shmulevich, E. Dougherty, 2003 .

Combining Dependent P-values with an Empirical Adaptation of Brown’s Method

David L. Gibbs, Ilya Shmulevich, William Poole, 2015, bioRxiv.

3. Inference of Model Structure

Edward R. Dougherty, Ilya Shmulevich, E. Dougherty, 2010 .

Inference of Boolean Networks Using Sensitivity Regularization

Edward R. Dougherty, Wenbin Liu, Ilya Shmulevich, 2008, EURASIP J. Bioinform. Syst. Biol..

Stability-based cluster analysis applied to microarray data

Ioan Tabus, Ilya Shmulevich, Wei Zhang, 2003, Seventh International Symposium on Signal Processing and Its Applications, 2003. Proceedings..

Propagating organization: an enquiry

Randy Goebel, Robert K. Logan, Ilya Shmulevich, 2007 .

5. External Control

Edward R. Dougherty, Ilya Shmulevich, E. Dougherty, 2010 .

The role of certain Post classes in Boolean network models of genetic networks

Jaakko Astola, Ilya Shmulevich, Edward R Dougherty, 2003, Proceedings of the National Academy of Sciences of the United States of America.

Literature-based discovery of new candidates for drug repurposing

Jung-Hsien Chiang, Ilya Shmulevich, Jiun-Huang Ju, 2016, Briefings Bioinform..

Almost all monotone Boolean functions are polynomially learnable using membership queries

Jaakko Astola, Ilya Shmulevich, Aleksey D. Korshunov, 2001, Inf. Process. Lett..

Scanners and Data Acquisition

Jaakko Astola, Ilya Shmulevich, Wei Zhang, 2005 .

From Boolean to probabilistic Boolean networks as models of genetic regulatory networks

Edward R. Dougherty, Wei Zhang, Ilya Shmulevich, 2002, Proc. IEEE.

Chapter Four. Classification

Edward R. Dougherty, Ilya Shmulevich, E. Dougherty, 2007 .

Cultivated Meat Modeling Consortium: Inaugural Meeting Whitepaper

Simon Kahan, Ilya Shmulevich, Jaromir Camphuijsen, 2020 .

Reliable learning using post classes

Moncef Gabbouj, Ilya Shmulevich, 2000, 2000 10th European Signal Processing Conference.

Correction of misclassifications in primary local image recognition using a nonlinear graph-based estimation technique

Vladimir V. Lukin, Ilya Shmulevich, Alexander N. Dolia, 2001, SPIE Remote Sensing.

On the Structure of Idempotent Monotone Boolean Functions

Ilya Shmulevich, Edward J. Coyle, 1998, NMBIA.

Flexibility of Boolean Network Reservoir Computers in Approximating Arbitrary Recursive and Non-Recursive Binary Filters

David L. Gibbs, Ilya Shmulevich, Boris Aguilar, 2018, Entropy.

Robust estimation of protein expression ratios with lysate microarray technology

Ioan Tabus, Ilya Shmulevich, Wei Zhang, 2005, Bioinform..

Multiscale mutation clustering algorithm identifies pan-cancer mutational clusters associated with pathway-level changes in gene expression

Ilya Shmulevich, William Poole, Theo A. Knijnenburg, 2017, PLoS Comput. Biol..

Biological Information as Set-Based Complexity

Nathan D. Price, Ilya Shmulevich, David J. Galas, 2010, IEEE Transactions on Information Theory.

Introduction to the special issue on information theory in molecular biology and neuroscience

Sean P. Meyn, Wojciech Szpankowski, Todd P. Coleman, 2010, IEEE Trans. Inf. Theory.

Generation of idempotent monotone Boolean functions

Ilya Shmulevich, 1998, 9th European Signal Processing Conference (EUSIPCO 1998).

On the distribution of the number of monotone Boolean functions relative to the number of lower units

Ilya Shmulevich, Aleksey D. Korshunov, 2002, Discret. Math..

Kernel density estimation with adaptive varying window size

Vladimir Katkovnik, Ilya Shmulevich, V. Katkovnik, 2002, Pattern Recognit. Lett..

The Role of Redundancy in the Robustness of Random Boolean Networks pdf

Carlos Gershenson, Ilya Shmulevich, Stuart A. Kauffman, 2005, ArXiv.

Iterative block-median pyramid transform-based denoising

Jaakko Astola, Karen O. Egiazarian, Ilya Shmulevich, 1999, Optics & Photonics.

Rhythm complexity measures for music pattern recognition

Dirk-Jan Povel, Ilya Shmulevich, 1998, 1998 IEEE Second Workshop on Multimedia Signal Processing (Cat. No.98EX175).

Microarray Quality Control: Zhang/Microarray Quality Control

Wei Zhang, Jaakko Astola, Ilya Shmulevich, 2005 .

Chapter Three. Stochastic Models of Gene Networks

Edward R. Dougherty, Ilya Shmulevich, E. Dougherty, 2007 .

Steady-State Analysis of Genetic Regulatory Networks Modelled by Probabilistic Boolean Networks

Edward R. Dougherty, Ilya Shmulevich, Wei Zhang, 2003, Comparative and functional genomics.

Perceptual Issues in Music Pattern Recognition: Complexity of Rhythm and Key Finding

Edward J. Coyle, Dirk-Jan Povel, Ilya Shmulevich, 2001, Comput. Humanit..

Solving the influence maximization problem reveals regulatory organization of the yeast cell cycle

David L. Gibbs, Ilya Shmulevich, I. Shmulevich, 2016, bioRxiv.

Moncef Gabbouj, Ilya Shmulevich, Bogdan Cramariuc, 2000, Proceedings 2000 International Conference on Image Processing (Cat. No.00CH37101).

An Integration Architecture Designed to Deal with the Issues of Biological Scope, Scale and Complexity

Ilya Shmulevich, John Boyle, Hector Rovira, 2010, DILS.

Using cell fate attractors to uncover transcriptional regulation of HL60 neutrophil differentiation

Ilya Shmulevich, Wei Zhang, Stuart A. Kauffman, 2009, BMC Systems Biology.

Output distributions of recursive stack filters

Jaakko Astola, Karen O. Egiazarian, Ilya Shmulevich, 1999, IEEE Signal Processing Letters.

Steady-state probabilities for attractors in probabilistic Boolean networks

Edward R. Dougherty, Marcel Brun, Ilya Shmulevich, 2005, Signal Process..

Pattern Processing in Music Analysis and Creation

Edward J. Coyle, Dirk-Jan Povel, Geraint A. Wiggins, 2001 .

Combination of transform based denoising and stack filtering for non-Gaussian noise suppression

Karen O. Egiazarian, Ilya Shmulevich, Vladimir P. Melnik, 1999, NSIP.

Complexity of the consistency problem for certain Post classes

Jaakko Astola, Moncef Gabbouj, Ilya Shmulevich, 2001, IEEE Trans. Syst. Man Cybern. Part B.

Critical Boolean networks require minimal intervention rate

Edward R. Dougherty, Wenbin Liu, Ilya Shmulevich, 2009, 2009 IEEE International Workshop on Genomic Signal Processing and Statistics.

Uncovering a Macrophage Transcriptional Program by Integrating Evidence from Motif Scanning and Expression Dynamics

Bin Li, Jared C. Roach, Alistair G. Rust, 2008, PLoS Comput. Biol..

Chapter Two. Deterministic Models of Gene Networks

Edward R. Dougherty, Ilya Shmulevich, E. Dougherty, 2007 .

Robust regression for periodicity detection in non-uniformly sampled time-course gene expression data

Ilya Shmulevich, Olli Yli-Harja, Harri Lähdesmäki, 2007, BMC Bioinformatics.

Reduction factors in finite automata with application to nonlinear filters

Pertti Koivisto, Antti Valmari, Ilya Shmulevich, 2000, 2000 10th European Signal Processing Conference.

EPEPT: A web service for enhanced P-value estimation in permutation tests

Ilya Shmulevich, John Boyle, Hector Rovira, 2011, BMC Bioinformatics.

2. Structure and Dynamics of Probabilistic Boolean Networks

Edward R. Dougherty, Ilya Shmulevich, E. Dougherty, 2010 .

Binary analysis and optimization-based normalization of gene expression data

Ilya Shmulevich, Wei Zhang, I. Shmulevich, 2002, Bioinform..

Graph-based smoothing of class data with applications in musical key finding

Ilya Shmulevich, Olli Yli-Harja, Kjell Lemström, 1999, NSIP.

Quantization and similarity measure selection for discrimination of lymphoma subtypes under k-nearest neighbor classification

Ioan Tabus, Masahiro Yamaguchi, Jaakko Astola, 2004, SPIE BiOS.

2009 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSiPS 2009, Minneapolis, MN, USA, May 17-21, 2009

Ganapati Panda, Aniruddha Datta, Edward R. Dougherty, 2009, GENSiPS.

6. Asynchronous Networks

Edward R. Dougherty, Ilya Shmulevich, E. Dougherty, 2010 .

A Note on the Pitch Contour Similarity Index

Ilya Shmulevich, I. Shmulevich, 2004 .

Probabilistic analysis of gene expression measurements from heterogeneous tissues

Pekka Ruusuvuori, Ilya Shmulevich, Harri Lähdesmäki, 2010, Bioinform..

Genome-wide histone acetylation data improve prediction of mammalian transcription factor binding sites

Stephen A. Ramsey, Ilya Shmulevich, Vladimir Litvak, 2010, Bioinform..

Robust quantification of in vitro angiogenesis through image analysis

Ilya Shmulevich, Olli Yli-Harja, Antti Niemistö, 2005, IEEE Transactions on Medical Imaging.

Genomic Signal Processing

Jaakko Astola, Ioan Tabus, Edward R. Dougherty, 2003, IEEE Signal Processing Magazine.

Fewer permutations, more accurate P-values

Marcel J. T. Reinders, Lodewyk F. A. Wessels, Ilya Shmulevich, 2009, Bioinform..

Send Orders of Reprints at Reprints@benthamscience.org on the Limitations of Biological Knowledge

Ilya Shmulevich, Edward R Dougherty, E. Dougherty, 2022 .

Set-based complexity and biological information pdf

Nathan D. Price, Ilya Shmulevich, David J. Galas, 2008, ArXiv.

Simplified implementation of the recursive median sieve

Gavin C. Cawley, Pertti Koivisto, Ilya Shmulevich, 2001, Signal Process..

Boolean Modeling of Biological Networks

Ilya Shmulevich, Peter M. Krawitz, I. Shmulevich, 2009, Encyclopedia of Complexity and Systems Science.

In silico microdissection of microarray data from heterogeneous cell populations

Ilya Shmulevich, Olli Yli-Harja, Wei Zhang, 2005, BMC Bioinformatics.

Spectral methods for testing membership in certain post classes and the class of forcing functions

Karen O. Egiazarian, Ilya Shmulevich, Harri Lähdesmäki, 2004, IEEE Signal Processing Letters.

Mapping dynamical states to structural classes for Boolean networks using a classification algorithm

Septimia Sarbu, Ilya Shmulevich, Olli Yli-Harja, 2015, 2015 23rd European Signal Processing Conference (EUSIPCO).

Markov Random Field Modeling in Median Pyramidal Transform Domain for Denoising Applications

Ilya Shmulevich, Vladimir P. Melnik, Ilya Gluhovsky, 2004, Journal of Mathematical Imaging and Vision.

Inference of Genetic Regulatory Networks via Best-Fit Extensions

Jaakko Astola, Ilya Shmulevich, Olli Yli-Harja, 2003 .

Mappings between probabilistic Boolean networks

Edward R. Dougherty, Ilya Shmulevich, 2003, Signal Process..

Learning the structure of dynamic Bayesian networks from time series and steady state measurements

Ilya Shmulevich, Harri Lähdesmäki, H. Lähdesmäki, 2008, Machine Learning.

Structure-Dynamics Relationships in Biological Networks

Matti Nykter, Ilya Shmulevich, Olli Yli-Harja, 2011 .

Probabilistic Boolean networks: a rule-based uncertainty model for gene regulatory networks

Edward R. Dougherty, Ilya Shmulevich, Seungchan Kim, 2002, Bioinform..

The ISB Cancer Genomics Cloud: A Flexible Cloud-Based Platform for Cancer Genomics Research.

David L. Gibbs, Ilya Shmulevich, Michael Miller, 2017, Cancer research.

Chapter One. Biological Foundations

Edward R. Dougherty, Ilya Shmulevich, E. Dougherty, 2007 .

Localized Key Finding: Algorithms and Applications

Ilya Shmulevich, Olli Yli-Harja, I. Shmulevich, 2000 .

Fastbreak: a tool for analysis and visualization of structural variations in genomic data

Ilya Shmulevich, John Boyle, Hector Rovira, 2012, EURASIP J. Bioinform. Syst. Biol..

Using image processing to determine the spatial dynamics of proteins and RNAs in single cells

Nicholas S. Flann, Stephen Marshall, Ilya Shmulevich, 2010 .

Systems biology driven software design for the research enterprise

Ilya Shmulevich, John Boyle, Christopher C. Cavnor, 2007, BMC Bioinformatics.

ADAPTS: Automated deconvolution augmentation of profiles for tissue specific cells

David L. Gibbs, Ilya Shmulevich, Alexander V Ratushny, 2019, PloS one.

Output distributions of stack filters based on mirrored threshold decomposition

Gonzalo R. Arce, Ilya Shmulevich, José L. Paredes, 2001, IEEE Trans. Signal Process..

Bioinformatic approaches and computational models for data integration and cross-species extrapolation in the postgenomic era

Ilya Shmulevich, Joshua M. Stuart, Michael D. Waters, 2006 .

Editorial

Kenneth E. Barner, Giovanni L. Sicuranza, Gonzalo R. Arce, 2002, EURASIP J. Adv. Signal Process..

Markov Random Field Modeling in Median Pyramidal Transform Domain for Denoising Applications

Ilya Shmulevich, Vladimir P. Melnik, Ilya Gluhovsky, 2001, IS&T/SPIE Electronic Imaging.

Introduction to the Issue on Genomic and Proteomic Signal Processing

Ioan Tabus, Dan Schonfeld, Ahmed H. Tewfik, 2008, IEEE J. Sel. Top. Signal Process..

Correction to "output distributionsof stack filters based on mirrored threshold decomposition"

Gonzalo R. Arce, Ilya Shmulevich, José L. Paredes, 2001, IEEE Trans. Signal Process..

Howdah - A Flexible Pipeline Framework for Analyzing Genomic Data

Mike O'Leary, Ilya Shmulevich, Hector Rovira, 2010, 2010 IEEE Second International Conference on Cloud Computing Technology and Science.

Critical networks exhibit maximal information diversity in structure-dynamics relationships.

Ilya Shmulevich, Olli Yli-Harja, Matti Nykter, 2008, Physical review letters.

A tree of median pyramidal decompositions with an application to signal denoising

Karen O. Egiazarian, Pauli Kuosmanen, Ilya Shmulevich, 2000, 2000 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.00CH37100).

Eukaryotic cells are dynamically ordered or critical but not chaotic.

Ilya Shmulevich, Stuart A Kauffman, Maximino Aldana, 2005, Proceedings of the National Academy of Sciences of the United States of America.

Optimization of stack filters using sample selection probabilities

Karen O. Egiazarian, Ilya Shmulevich, Vladimir P. Melnik, 1999, NSIP.

Correction of Misclassifications Using a Proximity-Based Estimation Method

Vladimir V. Lukin, Ilya Shmulevich, Olli Yli-Harja, 2004, EURASIP J. Adv. Signal Process..

1. Boolean Networks

Edward R. Dougherty, Ilya Shmulevich, E. Dougherty, 2010 .

Structure learning for Bayesian networks as models of biological networks.

Ilya Shmulevich, Harri Lähdesmäki, Antti Larjo, 2013, Methods in molecular biology.

Relationships between probabilistic Boolean networks and dynamic Bayesian networks as models of gene regulatory networks

Ilya Shmulevich, Sampsa Hautaniemi, Olli Yli-Harja, 2006, Signal Process..

SEQADAPT: an adaptable system for the tracking, storage and analysis of high throughput sequencing experiments

Stephen A. Ramsey, Ilya Shmulevich, John Boyle, 2009, BMC Bioinformatics.

Image denoising using a block-median pyramid

Jaakko Astola, Karen O. Egiazarian, Ilya Shmulevich, 1999, Proceedings 1999 International Conference on Image Processing (Cat. 99CH36348).

Genomic Signal Processing: The Salient Issues

Michael L. Bittner, Edward R. Dougherty, Ilya Shmulevich, 2004, EURASIP J. Adv. Signal Process..

Growing genetic regulatory networks from seed genes

Michael L. Bittner, Edward R. Dougherty, Ronaldo Fumio Hashimoto, 2004, Bioinform..

Biocellion: accelerating computer simulation of multicellular biological system models

Nicholas S. Flann, Seunghwa Kang, Simon Kahan, 2014, Bioinform..

Ayesian Automatic Relevance Determination Algorithms for Classifying Gene Expression Data

Edward R. Dougherty, Ilya Shmulevich, Wei Zhang, 2002, Bioinform..

Trade-off between Responsiveness and Noise Suppression in Biomolecular System Responses to Environmental Cues

Ilya Shmulevich, Alexander V. Ratushny, John D. Aitchison, 2011, PLoS Comput. Biol..

ProbCD: enrichment analysis accounting for categorization uncertainty

Ilya Shmulevich, Ricardo Z. N. Vêncio, I. Shmulevich, 2007 .

Using Incomplete Trios to Boost Confidence in Family Based Association Studies

David L. Gibbs, Ilya Shmulevich, Roger Kramer, 2016, Front. Genet..

Breakdown probabilities of recursive stack filters

Pertti Koivisto, Ilya Shmulevich, Olli Yli-Harja, 2001, Signal Process..

Simcluster: clustering enumeration gene expression data on the simplex space

Ilya Shmulevich, Ricardo Z. N. Vêncio, Leonardo Varuzza, 2007 .

RF-ACE for uncovering nonlinear associations from heterogeneous cancer data

Ilya Shmulevich, Olli Yli-Harja, Harri Lähdesmäki, 2011 .

On the robustness of the class of stack filters

Jaakko Astola, Ilya Shmulevich, Olli Yli-Harja, 2002, IEEE Trans. Signal Process..

Misclassification correction in primary local recognition of component images of multichannel remote sensing data

Vladimir V. Lukin, Ilya Shmulevich, Alexander N. Dolia, 2002, SPIE Remote Sensing.

Driver Fusions and Their Implications in the Development and Treatment of Human Cancers

Li Ding, Ilya Shmulevich, Matti Nykter, 2018, Cell reports.

Differential gene and protein expression in primary breast malignancies and their lymph node metastases as revealed by combined cDNA microarray and tissue microarray analysis

Chunlei Wu, Ilya Shmulevich, Harri Lähdesmäki, 2004, Cancer.

Average Sensitivity of Typical Monotone Boolean Functions

Ilya Shmulevich, 2005 .

A METHOD FOR CALCULATING BREAKDOWN PROBABILITIES OF RECURSIVE STACK FILTERS BASED ON MARKOV CHAIN MODELS

Pertti Koivisto, Ilya Shmulevich, Olli Yli-Harja, 1999 .

MiR‐506 suppresses proliferation and induces senescence by directly targeting the CDK4/6–FOXM1 axis in ovarian cancer

Ilya Shmulevich, Ping Ji, David Cogdell, 2014, The Journal of pathology.

The Cancer Microbiome: Distinguishing Direct and Indirect Effects Requires a Systemic View

Fiona Ginty, Mark P. Styczynski, Ilya Shmulevich, 2020, Trends in cancer.

Pathway alterations during glioma progression revealed by reverse phase protein lysate arrays

Ioan Tabus, Ilya Shmulevich, Yu Jia, 2006, Proteomics.

Biological Foundations

Edward R. Dougherty, Ilya Shmulevich, E. Dougherty, 2007 .

ACTIVE LEARNING OF BAYESIAN NETWORK STRUCTURE IN A REALISTIC SETTING

Ilya Shmulevich, Olli Yli-Harja, Antti Larjo, 2008 .

Molecular voting for glioma classification reflecting heterogeneity in the continuum of cancer progression.

Ioan Tabus, Ilya Shmulevich, Cristian Mircean, 2005, Oncology reports.

Multiscale Representation of Genomic Signals

Peter W. Laird, Stephen A. Ramsey, Ilya Shmulevich, 2014, Nature Methods.

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Clement Adebamowo, Ritika Kundra, Steven J. M. Jones, 2018, Cell reports.

Gene pair signatures in cell type transcriptomes reveal lineage control

Ilya Shmulevich, Matti Nykter, Merja Heinäniemi, 2013, Nature Methods.

Tumor specific gene expression profiles in human leiomyosarcoma

Ilya Shmulevich, Wei Zhang, Kenneth R Hess, 2002, Cancer.

The use of sample selection probabilities for stack filter design

Karen O. Egiazarian, Ilya Shmulevich, Vladimir P. Melnik, 2000, IEEE Signal Processing Letters.

Data extraction from composite oligonucleotide microarrays.

Wei Zhang, Jaakko Astola, Ilya Shmulevich, 2003, Nucleic acids research.

Differing clinical impact of BRCA1 and BRCA2 mutations in serous ovarian cancer.

Ilya Shmulevich, Yan Sun, Wei Zhang, 2012, Pharmacogenomics.

Integrated Analysis of Gene Expression and Tumor Nuclear Image Profiles Associated with Chemotherapy Response in Serous Ovarian Carcinoma

Ilya Shmulevich, Yan Sun, Wei Zhang, 2012, PloS one.

Association of Somatic Mutations of ADAMTS Genes With Chemotherapy Sensitivity and Survival in High-Grade Serous Ovarian Carcinoma.

Li Ding, Ilya Shmulevich, Gordon B Mills, 2015, JAMA oncology.

POMO - Plotting Omics analysis results for Multiple Organisms

Ilya Shmulevich, Matti Nykter, Patrick May, 2013, BMC Genomics.

Kinetic Inference Resolves Epigenetic Mechanism of Drug Resistance in Melanoma

Jie Chen, Ilya Shmulevich, David Baltimore, 2019, bioRxiv.

Bright Field Microscopy as an Alternative to Whole Cell Fluorescence in Automated Analysis of Macrophage Images

Pekka Ruusuvuori, Ilya Shmulevich, Olli Yli-Harja, 2009, PloS one.

Properties and applications of monotone Boolean functions and stack filters

Ilya Shmulevich, 1997 .

Unsupervised Analysis Uncovers Changes in Histopathologic Diagnosis in Supervised Genomic Studies

Ilya Shmulevich, Olli Yli-Harja, Matti Nykter, 2006, Technology in cancer research & treatment.

Distinguishing key biological pathways between primary breast cancers and their lymph node metastases by gene function-based clustering analysis.

Wei Zhang, Ilya Shmulevich, Olli Yli-Harja, 2004, International journal of oncology.

Entropy of complex relevant components of Boolean networks.

Ilya Shmulevich, Peter Krawitz, 2007, Physical review. E, Statistical, nonlinear, and soft matter physics.

Identification of copy number variants in whole-genome data using Reference Coverage Profiles

Jared C. Roach, Gustavo Glusman, Max Robinson, 2015, Front. Genet..

Microarray reveals differences in both tumors and vascular specific gene expression in de novo CD5+ and CD5- diffuse large B-cell lymphomas.

Ilya Shmulevich, Wei Zhang, Edward Suh, 2003, Cancer research.

Erratum: The somatic genomic landscape of glioblastoma (Cell (2013) 155 (462-477))

Chris Sander, David Haussler, Wei Zhang, 2014 .

Integrated analyses identify a master microRNA regulatory network for the mesenchymal subtype in serous ovarian cancer.

Ilya Shmulevich, Wei Zhang, Matti Nykter, 2013, Cancer cell.

Augmentation of response to chemotherapy by microRNA-506 through regulation of RAD51 in serous ovarian cancers.

Ilya Shmulevich, Yan Sun, Ping Ji, 2015, Journal of the National Cancer Institute.

Combining Dependent P-values with an Empirical Adaptation of Brown’s Method

David L. Gibbs, Ilya Shmulevich, Brady Bernard, 2015 .

The Innate Immune Database (IIDB)

Bin Li, Hamid Bolouri, Vesteinn Thorsson, 2008, BMC Immunology.

A multilevel pan-cancer map links gene mutations to cancer hallmarks

Lodewyk F. A. Wessels, Ilya Shmulevich, Theo A. Knijnenburg, 2015, Chinese journal of cancer.

Clinical significance of CTNNB1 mutation and Wnt pathway activation in endometrioid endometrial carcinoma.

Li Ding, Ilya Shmulevich, Wei Zhang, 2014, Journal of the National Cancer Institute.

Role of the transcription factor C/EBPδ in a regulatory circuit that discriminates between transient and persistent Toll-like receptor 4-induced signals

Alistair G. Rust, Stephen A. Ramsey, Ilya Shmulevich, 2009, Nature Immunology.