Welcome to BioData Mining Lab
BioData Mining Lab performs research in the areas of Bioinformatics, Data Mining, and Machine Learning. We development methods and algorithms for mining and inferring biological data of various types (variety) both small and large (volume) with the emphasis on improved explainability (interpretability). I apply the methods to solve various precision medicine problems such as genomic profiling, cancer stratification, and disease gene prioritization.
- Integrative Analysis (Variety).
- - Heterogeneous data integration
- - Tensor mining
- - Multiple kernel learning
- Scalable Methods (Volume)
- - Tensor decomposition
- - Graph ranking
- - L1 loss minimization
- Explainable models (Interpretability)
- - Causal gene prioritization through protein structure
- - Pattern extraction of ICU signals via Convolution Neural Network
- - Graphical models
The lab also has expertise in the working with 3D protein structures with the focus of application on computation drug development.
- - Protein structure search
- - Target detection & Adverse drug effects prediction
- - Integrative structure prediction
We face a new era of challenges due to fast growing data accumulation of both biological and medical data at various levels of biological processes. For this reason and more, the role of computer scientists whom are specialized in computational biology and bioinformatics is becoming more important.
If you are a prospective student or a postdoc, we welcome you to contact (e-mail prefered). All who are interested in joining the lab should send me an email with your full Curriculum Vitae and a short Research Statement. Also, we are always looking for collaborations, so please contact!