I am a Computer Science PhD candidate at WPI KorkinLab (Korkin lab) under supervision of Dmitry Korkin. My research is centered around proteomics with an emphasis on network analysis and machine learning. In particular, I am working on application of machine learning models to answer the question how alternative splicing reshapes human interactome. I am looking for postdoc positions in my field and I am open to collaboration.
Currently I work on the following projects:
- ALT-IN Tool - project to build machine learning model for prediction of gene isoforms interactions. It leverages existing interactome data and includes alternative splicing-specific information. I analyzed several machine learning approaches, including utilization of Learning Under Privileged Information (LUPI) paradigm. I handled machine learning-related tasks, a part of data extraction and case study analysis and produces deliverables publicly available on GitHub and DockerHub .
- Clinical trials of Gulf War Illness treatment - I was responsible for identifying gene set that exhibit response to acupuncture treatment based on SomaScan proteomics data. First, I evaluated different strategies for intra- and interplate normalization. Then I employed a range of statistical methods and successfully identified relevant genes. This discovery was further supported by literature search. I also conducted a preliminary work on biomarkers identification of the successful treatment. This work was done as a part of a joint grant application.
- Molecular dynamics of SARS-CoV-2 envelope - Ongoing project close to the completion. Collaborative effort on bringing together accuate stoichiometry, geometry, and structural information on SARS-CoV-2 envelope. My responsibilities include part of the structural modeling of membrane (M) protein and system integration, as well as performing molecular dynamics simulations on Frontera supercomputer and network analysis on protein connectivity.