BINC BioInformatics Syllabus- Advanced
Sequence analysis
Scoring matrices: Detailed method of derivation of the PAM and BLOSUM matrices
Pairwise sequence alignments: Needleman and Wuncsh, Smith and Waterman algorithms and their implementation
Multiple sequence alignments (MSA): Use of HMM-based Algorithm for MSA (e.g. SAM method)
Taxonomy and phylogeny: Phylogenetic analysis algorithms such as maximum Parsimony, UPGMA, Transformed Distance, Neighbors-Relation, Neighbor-Joining, Probabilistic models and associated algorithms such as Probabilistic models of evolution and maximum likelihood algorithm, Bootstrapping methods, use of tools such as Phylip, Mega, PAUP
Sequence patterns and profiles:
Algorithms for derivation of and searching sequence patterns: MeMe, PHI-BLAST, SCanProsite and PRATT
Algorithms for generation of sequence profiles: Profile Analysis method of Gribskov, HMMer, PSI-BLAST
Protein and nucleic acid properties: e.g. Proteomics tools at the ExPASy server and GCG utilities and EMBOSS
Structural Biology
Identification/assignment of secondary structural elements from the knowledge of 3-D structure of macromolecule using DSSP and STRIDE methods
Prediction of protein structure: PHD and PSI-PRED methods
Tertiary structure: Detailed protocols/algorithms for Homology modeling, fold recognition and ab-initio approaches
Structures of oligomeric proteins and study of interaction interfaces
Molecular modeling and simulations
Macro-molecular force fields, salvation, long-range forces
Geometry optimization algorithms: Steepest descent, conjugate gradient
Various simulation techniques: MD, Monte Carlo, docking strategies etc
Molecular mechanics, conformational searches
Genomics
Large scale genome sequencing strategies
Genome assembly and annotation
Genome databases of Plants, animals and pathogens
Metagenomics
Gene networks: basic concepts, computational model such as Lambda receptor and lac operon
Prediction of genes, promoters, splice sites, regulatory regions: basic principles, application of methods to prokaryotic and eukaryotic genomes and interpretation of results
Basic concepts on identification of disease genes, role of bioinformatics-OMIM database, reference genome sequence, integrated genomic maps, gene expression profiling; identification of SNPs, SNP database (DbSNP). Role of SNP in Pharmacogenomics, SNP arrays
Basic concepts in identification of Drought stress response genes, insect resistant genes, nutrition enhancing genes
Epigenetics
DNA microarray: database and basic tools, Gene Expression Omnibus (GEO), ArrayExpress, SAGE databases
DNA microarray: understanding of microarray data, normalizing microarray data, detecting differential gene expression, correlation of gene expression data to biological process and computational analysis tools (especially clustering approaches)
Comparative genomics:
Basic concepts and applications, BLAST2, MegaBlast algorithms, PipMaker, AVID, Vista, MUMmer, applications of suffix tree in comparative genomics, synteny and gene order comparisons
Comparative genomics databases: COG, VOG
Functional genomics:
Application of sequence based and structure-based approaches to assignment of gene functions – e.g. sequence comparison, structure analysis (especially active sites, binding sites) and comparison, pattern identification, etc. Use of various derived databases in function assignment, use of SNPs for identification of genetic traits
Gene/Protein function prediction using Machine learning tools viz. Neural network, SVM etc
Proteomics
Protein arrays: basic principles
Computational methods for identification of polypeptides from mass spectrometry
Protein arrays: bioinformatics-based tools for analysis of proteomics data (Tools available at ExPASy Proteomics server); databases (such as InterPro) and analysis tools
Protein-protein interactions: databases such as DIP, PPI server and tools for analysis of protein-protein interactions
Modeling biological systems
Systems biology – Use of computers in simulation of cellular subsystems
Metabolic networks, or network of metabolites and enzymes
Metabolic pathways: databases such as KEGG, EMP
Study of plant pathways –MetaCyc, AraCyc
Signal transduction networks
Gene regulatory networks
Bioinformatics Resources at the species level
ICTV Database, AVIS, VirGen, Viral genomes at NCBI, VBRC, VBCA, PBRC and Subviral RNA database, Species 2000, TreeBASE etc
Drug design
Drug discovery process
Role of Bioinformatics in drug design
Target identification and validation, lead optimization and validation
Structure-based drug design and ligand based drug design
Modeling of target-small molecule interactions
Vaccine design:
Reverse vaccinology and immunoinformatics
Databases in Immunology
B-cell epitope prediction methods
T-cell epitope prediction methods
Resources to study antibodies, antigen-antibody interactions
Structure Activity Relationship – QSARs and QSPRs, QSAR Methodology, Various Descriptors used in QSARs: Electronics; Topology; Quantum Chemical based Descriptors. Use of Genetic Algorithms, Neural Networks and Principle Components Analysis in the QSAR equations
Bio-Informatics National Certification (BINC) 2019 Syllabus