Bioinformatics pipeline tools | Flow cytometry analysis

Dr. Yashwanth Subbannayya obtained his M.Sc. degree in Medical Biochemistry from Manipal University. He qualified the competitive CSIR-UGC National Eligibility Test and joined the Institute of Bioinformatics, Bangalore as a UGC Junior Research Fellow. As part of his Ph.D. work, he studied the molecular mechanisms of gastric cancer in clinical specimens using quantitative proteomic technologies. This study, the results of which were published in Cancer Biology and Therapy, yielded a novel therapeutic target for gastric cancer- CAMKK2. Further, he also studied the serum proteome of gastric cancer patients and developed assays for potential markers using the revolutionary multiple reaction monitoring approach. The results of this study were published in Journal of Proteomics. In addition to his research work, he also trained extensively in sample preparation for mass spectrometry, fractionation techniques and gained expertise in quantitative proteomic techniques and data analysis. In addition, he also trained extensively in various validation platforms including immunohistochemsitry, multiple reaction monitoring and Western blot. He has also worked as a curator for several biological databases including NetPath, Human Protein Reference Database (HPRD) and Breast cancer database. His work in various research projects have yielded him 23 publications either as lead author or co-author in peer reviewed journals. He is a reviewer for the journal Proteomics. Dr. Yashwanth Subbannayya joined the YU-IOB Center for Systems Biology and Molecular Medicine in June, 2015. During the initial period, his job consisted of assisting other personnel of the university in the establishment of YU-IOB Center for Systems Biology and Molecular Medicine. He was also involved in training of Ph.D. students in biological aspects. After the establishment of the center, he trained in cell culture techniques and metabolomics analysis. At YU-IOB CSBMM, he is studying the molecular mechanisms in various cancers including oral cancer. In addition, he is studying the molecular mechanisms as well as the metabolic constituents of traditional medicine formulations using mass spectrometry technologies. In June 2016, he convened the national symposium “Genomics in clinical practice: Future of precision medicine” held at Yenepoya University on June 1 and 2, 2016. The resource persons included 16 individuals from various academic organizations as well as industry. The symposium was attended by 218 participants from 24 institutions around India. He is a member of the Scientific Review Board of Yenepoya Research Centre where he facilitates timely scientific review of research projects.

Bioinformatics workflow tools | Flow cytometry data analysis

Automation technologies developed during the last several years have enabled the use of flow cytometry (FCM) to generate large, complex data sets in both basic and clinical research applications (Brinkman et al., 2007). A serious bottleneck in the interpretation of existing studies and the application of high throughput FCM to even larger, more complex problems is that data management and data analysis methods have not advanced sufficiently far from the methods developed for applications of FCM to small-scale, tube-based studies [2]. In particular, the data often need to be organized into groups of samples based on combinations of additional covariates and similar operations need to be applied to these groups in a transparent and reproducible manner. Furthermore, the growing depth of knowledge in the field of immunology, for instance the characterization of distinct human T-cell sub-population [3], clearly argues for more systematic approaches.

Source text:
(Hahne et al., 2009) flowCore: a Bioconductor package for high throughput flow cytometry. BMC Bioinformatics.
(Brinkman et al., 2007) High-Content Flow Cytometry and Temporal Data Analysis for Defining a Cellular Signature of Graft-Versus-Host Disease. Biology of Blood and Marrow Transplantation.
(Mahnke et al., 2007) Optimizing a Multicolor Immunophenotyping Assay. Clinics in Laboratory Medicine.