The current members of the Systems Biology of Drug Resistance in Cancer group.
I work as a senior researcher in the Hautaniemi Lab. The focus of the research group is to understand and find effective means to overcome drug resistance in cancers, especially in High Grade Serous Ovarian Cancer. Although I am participating in most of the projects in the lab I am particularly interested in using multi-omics sequencing data to gain understanding of tumor heterogeneity and evolution in chemoresistance. Biological and clinical interpretation of results from genomics and genetics data is crucial part of my work.
My work involves developing statistical methods for analysis and integration of ovarian cancer data at multiple levels to suggest efficient combinatorial treatments.
I'm focusing on genetic analyses and tumor evolution.
The cancer genome is my broad interest, specifically, understanding the genomic mechanisms governing cancer progression and leading to recurrence and drug resistance. I am involved in several projects studying high-grade serous ovarian cancer, breast cancer and diffuse large B-cell lymphoma. Cancer evolution, intra-tumor heterogeneity, mutational processes and genome instability are all among my research interests. I also work on development of computational pipelines to analyze cancer genomes for somatic mutations, copy number alterations and structural rearrangements.
My main interest is on the molecular mechanisms and markers that regulate chemoresistance in cancer. My research is focused on machine learning approaches to mass cytometry (CyTOF), proteomics, and genomics data of high grade serous ovarian cancer samples.
My research is focused on finding driving mechanisms in cancer and other diseases using genomic and transcriptomic data. I am also interested in testing and developing methods for RNA-Seq data analysis.
My projects focus identifying epigenetic mechanisms responsible for drug resistance in cancer. I work with bisulfite sequencing data in order to analyze DNA methylation patterns in Diffuse Large B-Cell Lymphoma (DLBCL) and High-Grade Serous Ovarian Cancer (HGSOC). I am also involved in a drug screening project where we are testing different epigenetic inhibitors to re-sensitize DLBCL cell lines that are resistant to the standard treatment.
My current job is to develop ways to predict ovarian cancer outcome and determine optimal treatment strategy using clinical and genetic data. The work involves automating clinical data downloading from Turku University Hospital's electronic health records and combining it with other research data. I am also developing clinical data visualization and creating a machine learning approach to clinical data analysis.
My current projects focus on mathematical modeling to understand treatment resistance in ovarian cancer.
My main interest is on the cancer transcriptomics, at both single-cell and bulk level, to understand the mechanisms leading to chemoresistance in ovarian cancer. I am also working on the development of computational pipeline to analyze circulating tumor DNA for somatic and germline mutations.
I am visiting the lab for my Master's thesis project. My project is focused on developing an automated image analysis technique to predict which patients with High-Grade Serious Ovarian Cancer (HGSOC) can benefit from platinum-taxane treatment.
I am visiting the lab for my master thesis in computer science engineering. My work is focused on the design and implementation of algorithms for the detection and the analysis of long non-coding RNAs which show correlation to progression and chemotherapy response in High Grade Serous Ovarian Cancer (HGS-OvCa) using RNA-sequencing data.
My research interests revolve mainly around chemotherapy-induced toxicity in ovarian cancer patients. I am involved in the analysis of circulating tumour DNA for germ line and somatic mutations, and maintaining an oncology database.
I'm implementing, integrating and evaluating tools for data analysis and visualization.
I am working on data visualization.
My project is about finding ways to detect copy number variations in ctDNA.
Consulting the lab on infra related issues.