Repo

Comprehensive analysis of the TCR repertoire for a large group of donors.

We analyzed:

• Gene usage distribution of the TRA and TRB chains for the identification of deletions

• Co-expression factors for V-V, J-J, V-J pairs within and between TRA and TRB chains

• Genes usage between only functional and non-functional sequences to identify thymus selection

• We also compared found patterns between populations

• Skills: Python (scipy, statsmodels, numpy, pandas, matplotlib, seaborn, re, os), Bash, Jupyterhub, Conda, Biological databases (IMGT).
  

Repo

Development of a new representation of proteins for comparing structures with a focus on the secondary structures distribution.

• New representation of protein molecules using the distributions of secondary structures along their chains was developed

• Proteins from PDB were divided into groups according to function and homology

• Frequencies of occurrence of various secondary structures for the selected groups were compared

• Skills: Python (biotite, numpy, pandas, matplotlib, seaborn, re, os), Bash, Conda, Biological databases (PDB, CATH, UniProt, NCBI, PFam, GO).
  

Repo

Analyzing transcriptomic data from melanoma samples to identify trends in gene expression and building a model to predict overall survival based on expression levels.

• The study of clinical and transcriptomic data of patients with melanoma to identify patient groups and their patterns

• Transcriptomic signatures were selected based on a literature review and Cox regression to predict overall patient survival

• A survival prediction model using Cox regression has been developed

• Skills: R (survival, survminer, glmnet, ComplexHeatmap, tidyverse, gtsummary, factoextra, ggbiplot, ggplot2, ggpubr, dplyr, plotly, tibble, matrixStats), Biological databases (TCGA, GO).