SBL600
| SBL600 | |
|---|---|
| Computational Biology and Data Analyses | |
| Credits | 4 |
| Structure | 1-0-6 |
| Pre-requisites | SBL510 |
| Overlaps | |
SBL600 : Computational Biology and Data Analyses
[edit]Basics of data: Introduction; biological sequence data sources and handling methods; sequence alignment: pairwise, multiple and local alignment, BLAST, pattern search, phylogenetics and evolutionary tree search, machine learning methods in sequence analysis; data retrieval from GEO and other databases- different formats of sequencing data; microarray technologies - differential gene expression analyses by microarrays, modelling DNA microarray data, network analyses; next-generation sequencing; variants of NGS- transcriptome, exome, ChIP-seqmethods and different challenges in data analyses; nanopore sequencing technology; genome sequence assembly- de novo, assembly methods and error correction; microbial genomics; OMICs methods and practices; Proteomics technologies; quantitative and qualitative proteomics; label-free and SILAC based quantifications; environmental proteomics- filtering and cleaning of MS data; case- studies with data accessed from MS data servers; omics data analyses pipelines- quality control, omics data analyses pipelines- quality control, logtransformation and normalization of omics data, file formats, algorithms, data visualization, PCA and statistical analyses; biomolecular structure determination methods; long range forces and potentials; structure visualization, coordinate systems; structure data repository and retrieval; structure prediction: ab-initio method, comparative protein structure modelling, ligand-protein interaction, ligand docking; basics of protein structural dynamics; metabolic networks: network model building, flux analyses, systems biology approaches: microscopy data – fixed and live-cell imaging, time-lapse videos, dyes and resolution, super-resolution microscopy.