Plewczynski Lab

RESEARCH FIELDS

Fields of research in lab

STRUCTURAL GENOMICS

We perform theoretical and experimental studies to analyze and predict the 3D structure of the human genome.

FUNCTIONAL GENOMICS

We examine the relationship of the expression levels of selected genes from their location in 3D space.

DATA MINING, BIOSTATISTICS

To make sense of complex biological data, we apply machine learning techniques to extract multidimensional dependencies.

Deep Learning

We use Deep Learning models for prediction of genetic features based on the sequence.

Bioinformatics Services

Bioinformatics services offered in our laboratory.

Services

3dFlu

3DFlu is a comprehensive database designed to provide useful information regarding hemagglutinin proteins (HAs) of influenza virus type A.

3dgnome

The web-service that allows for creating 3D models of the genomic regions and their interactive visualization, as well as for a simple explorative data analysis.

Spring Model

Spring model is a webservice for modelling chromatin domains using direct information about contacts derived from experiments like Hi-C or ChIA-PET. It is employs polymer physics and molecular mechanics using OpenMM library.

ConsensuSV

Automatised pipeline of ConsensuSV workflow, going from raw sequencing Illumina data (fastq), to output vcf files.

Areas For Scientific Synergies

Three dimensional Genomics, 4DNucleome related projects, the higher order chromatin organization; Hi-C / ChIA-PET / Hi-ChIP experiments and data analysis, chromatin looping, topologically associating domains, compartmentalization of nucleus, lamina and subnuclear structures interactions with chromatin; genome wide association studies (GWAS), structural variants identification and functional analysis (including deletions, duplications, insertions, inversions, and translocations), next generation sequencing, short (Illumina) and long-reads (Oxford Nanopore, PacBio) DNA sequencing and data analysis, ChIP-seq data analysis from the 3D structure perspective; Big Data, statistical learning, massive dataset analysis, Computational Genomics and bioinformatics in population-level genomic data for medical applications and fundamental research in Life Sciences, structural and functional analysis of “omics” data; biophysical simulations , polymer modeling, DNA, RNA and proteins structure prediction, protein-protein, protein-DNA, protein-RNA and RNA-DNA interactions: prediction and analysis of biomolecular interactions networks; whole-cell systems biology modeling;

Three-dimensional Human Genome structure at the population scale: computational algorithm and experimental validation for lymphoblastoid cell lines of selected families from 1000 Genomes

Project TEAM - Laboratory of Functional and Structural Genomics CeNT

Spatial network model of sequence and structure diversity of Human genome at a population scale

Dariusz Plewczyński

Multiscale spatial reorganization of chromatin in response to replication stress and its role in cellular protection against genomic instability

Dariusz Plewczyński

The (MSCA)-ITN the Innovative Training Networks program ENHPATHY

Dariusz Plewczyński

HPC facility

Dariusz Plewczyński

Bat Coronaviruses as an emerging threat for human population

Michał Łaźniewski

A complex programme of support for UW PhD students - Travel grant

Kaustav Sengupta