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Inducted as member of the "Big Data & Analytics" section of the "Bioinformatics, Biomedical Informatics & Computational Biology" area.

Member of Faculty Opinions

CAID is a worldwide competition that identifies the most accurate methods that predict the intrinsically disordered protein regions. The results were recently published in Nature Methods (https://www.nature.com/articles/s41592-021-01117-3), followed by a commentary article in the same journal that highlights our win (https://www.nature.com/articles/s41592-021-01123-5).

Author of the winning flDPnn algorithm of the international Critical Assessment of Protein Intrinsic Disorder Prediction (CAID) challenge

With citation for "outstanding achievements and contributions to the Polish scientific community."

Fellow of the Kosciuszko Foundation Collegium of Eminent Scientists

With citation for "outstanding contributions to structural bioinformatics, focusing on protein-ligand and protein-nucleic acids interactions and computational characterization of intrinsic disorder. "

Fellow of the American Institute for Medical and Biomedical Engineering (AIMBE)

Elevated to be a senior member of Association for Computing Machinery.

Senior Member of ACM

Recognition for outstanding academic achievements in the undergraduate and Master's studies.

Gold Medal of Stanislaw Staszic

Outstanding Graduate Student Award for the M.Sc. thesis.

Outstanding Graduate Student Award

Professor  Department of Computer Science  Virginia Commonwealth University

Adjunt Professor  Department of Electrical and Computer Engineering  University of Alberta

Intrinsic Disorder in Human RNA-Binding Proteins

flDPnn: Accurate intrinsic disorder prediction with putative propensities of disorder functions

DescribePROT: database of amino acid-level protein structure and function predictions

IDPology of the living cell: intrinsic disorder in the subcellular compartments of the human cell

DEPICTER: Intrinsic Disorder and Disorder Function Prediction Server

Taxonomic Landscape of the Dark Proteomes: Whole-Proteome Scale Interplay Between Structural Darkness, Intrinsic Disorder, and Crystallization Propensity

DRNApred, fast sequence-based method that accurately predicts and discriminates DNA- and RNA-binding residues

Disordered Nucleiome: Abundance of Intrinsic Disorder in the DNA- and RNA-binding Proteins in 1121 Species from Eukaryota, Bacteria and Archaea

Molecular Recognition Features (MoRFs) in Three Domains of Life

PDID: Database of Molecular-level Putative Protein-drug Interactions in the Structural Human Proteome

A Comprehensive Comparative Review of Sequence Based Pedictors of DNA and RNA Binding Residues

High-throughput prediction of RNA, DNA and protein binding regions mediated by intrinsic disorder

Comprehensive overview and assessment of computational prediction of microRNA targets in animals

Exceptionally abundant exceptions: comprehensive characterization of intrinsic disorder in all domains of life

Human structural proteome-wide characterization of Cyclosporine A targets

Interplay Between the Oxidoreductase PDIA6 and microRNA-322 Controls the Response to Disrupted Endoplasmic Reticulum Calcium Homeostasis

Disordered Proteinaceous Machines

Resilience of death: intrinsic disorder in proteins involved in the programmed cell death

CMSC 435 Introduction to Data Science

CMSC 635 Knowledge Discovery and Data Mining

ECE 321 Software Requirements Engineering

ENCMP 100 Computer Programming for Engineers

EE 280 Introduction to Digital Logic Design

CMPE 310 Applying Software Engineering Practices Project

ECE 625 Data Analysis and Knowledge Discovery

ECE 625 Advanced Data Analysis and Decision Making

CSC 4811 Computer Security

CSC 5728 Software Engineering

Lukasz Kurgan received his M.Sc. degree (with honors) in Automation and Robotics from AGH University of Science and Technology (Poland) in 1999 and a Ph.D. degree in Computer Science from University of Colorado at Boulder in 2003. He joined the University of Alberta in 2003 where he received tenure in 2007 and was promoted to the rank of Professor in 2013. He moved to the Virginia Commonwealth University in 2016 as the Robert J. Mattauch Endowed Professor of Computer Science.

Structural Bioinformatics

Intrinsically Disordered Proteins

Protein-ligand(drug) interactions

Computer-aided molecular modeling 

Big Data Analysis

Drug Repurposing

Drug Repositioning

Structural Genomics

BIOMINE laboratory

Google Scholar profile

ORCID

ResearcherID profile

Faculty Opinions member

Publons

LinkedIn

Computer science research team gains international recognition for method that accurately predicts intrinsic disorder in proteins

VCU professors join elite bioengineering institute

Lukasz Kurgan, Ph.D., with a picture of an intrinsically disordered protein behind him. Kurgan has developed bioinformatics computer programs that help determine the functions of these proteins.

VCU's Kurgan supercomputer programs help biologists to speed up hypothesis generation to understand proteins

Bioinformatics computer programs help biologists understand intrinsically disordered proteins

Unravelling the Complexity of Proteins

Crystallography for Complete Proteomes

Zeroing In...

Integrated prediction of intrinsic disorder and disorder functions with modular multi-label deep learning

High-throughput annotation of cellular functions of intrinsic disorder in proteins

High-throughput characterization, prediction, and applications of protein disorder

Early prediction of patient-related and radiological outcomes in patients with recent-onset inflammatory polyarthritis (EPA) using established and novel independent predictors

Molecular-level prediction and mitigation of side effects of tubulin-targeting cancer therapy drugs

Computational intelligence based platform for prediction and characterization of binding sites in proteins

Role of osteoclastogenesis and osteoclast activation in joint destruction in degenerative and inflammatory joint diseases

Dean Robert J. Mattauch Chair | Vice Chair of Computer Science

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