Fedor Kolpakov

Cross-platform DNA motif discovery and benchmarking to explore binding specificities of poorly studied human transcription factors

The paper evaluates cross-platform DNA motif discovery tools using 4,237 experiments to identify reliable transcription factor binding motifs and highlights challenges in motif detection.

Prediction and annotation of alternative transcription starts and promoter shift in the chicken genome

The paper predicts and annotates alternative transcription starts and promoter shifts in the chicken genome using CAGE data, revealing that housekeeping genes may use single sharp promoters and undergo significant promoter shifts.

Statistical framework for calling allelic imbalance in high-throughput sequencing data

The paper introduces MIXALIME, a statistical framework for detecting allele-specific events in sequencing data, and demonstrates its application in constructing an atlas of allele-specific chromatin accessibility.

A modular model of immune response as a computational platform to investigate a pathogenesis of infection disease

The paper develops a modular mathematical model of the immune response to SARS-CoV-2 infection to better understand disease progression and immune system behavior.

Mathematical modeling of the influence of ACE I/D polymorphism on blood pressure and antihypertensive therapy

This study uses a computational model to examine how the ACE I/D polymorphism affects blood pressure and antihypertensive therapy efficacy, finding limited predictive value of the variant.

A model of exercise-induced changes in metabolism, signaling, and gene expression in skeletal muscle

The paper develops a computational model to understand how exercise affects metabolism, signaling, and gene expression in skeletal muscle by integrating metabolic, signaling, and gene regulatory pathways.

Landscape of allele-specific transcription factor binding in the human genome

The paper identifies allele-specific transcription factor binding events across the human genome using ChIP-Seq data, revealing regulatory variants linked to disease and molecular mechanisms.