Bioinformatics

1. Introduction to Basics of Bioinformatics 2. Biological Databases and their Applications 3. Biological Sequence Analysis 4. Genome Assembly and Annotation 5. Computational Molecular Phylogeny: Concepts and Applications 6. Applications and challenges of microarray and RNA-sequencing 7. RNAseq Data Analysis 8. Analysis of SSR and SNP Markers 9. Gene Ontology (GO): Application and Importance in Functional Annotation of the Genomic Data 10. Metagenomics: The Boon for Microbial World Knowledge and Current Challenges 11. Protein structure Prediction 12. Structural and Functional analysis of protein 13. Computational Approaches in Drug designing 14. Structure-Based Drug Designing 15. Ligand-Based Drug Designing 16. Discovery and Optimization of Lead Molecules in Drug Designing 17. Pharmacophore modeling and its applications 18. Molecular Docking and Molecular Dynamics Simulation 19. Pharmacokinetics and Pharmacodynamics analysis of Drug Candidates 20. Computational Approaches for Vaccine Designing 21. Metabolomics and Flux Balance Analysis 22. Topological Parameters, Patterns, and Motifs in Biological Networks 23. Network Biology and its Application 24. Pathway Modeling and Simulation Analysis 25. Systems Biology and Big Data Analytics 26. Machine Leaning in Bioinformatics 27. Bioinformatics and Biological Data mining

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• Saude pessoal e pública
• Gestão da industria biotecnologica

bioinformatics; systems biology; database; health data; genome assembly; RNA sequencing; drug design; protein analysis; big data; machine learning; 13C metabolic flux analysis; 3D structure assessment; ADMET; Ab initio; Ab initio folding; Algorithms; Allele-specific expression; Annotation; Assembly; B-cell epitope; BLAST; BLOSUM; Bayesian phylogeny; Binding site; Binding-free energy; Bioinformatics; Biological data; Biological database; Biological databases; Biological network; Biological pathways; CADD; CDNA library; COPASI; Cell designer; Clade; Classification; Comparative modeling; Computational biology; Computational drug designing; Computational technology; Constraint-based analysis; Contigs; Copy number variants; Cytoscape; DNA; Data analysis; Data integration; Data mining; Data quality check; Database; Dataset; Deep learning; Descriptors; Differential gene expression; Docking; Drug design; Drug designing; Drug discovery; Drug repositioning; Drug repurposing; Drug target; EMBL; EQTL; Enrichment analysis; Evolution; Feature selection; Flux balance analysis; Function prediction; Functional assignment; Gene Ontology; Gene coexpression network; Gene prediction; Gene regulatory network; Genome; Genome annotation; Genomics; Global alignment; Graph theory; Health care; High-throughput experiments; Homology; In silico; In silico biology; KEGG; LBDD; Lead molecules; Lead optimization; Local alignment; MM-PBSA; Machine learning; Mass spectrometry; Maximum likelihood; Metabolic modeling; Metabolic network; Metabolic reconstruction; Metabolomics; Metagenomic; Microarray; Microbial taxonomy; Mining tools; Molecular docking; Molecular dynamics simulation; Motif; Multiple sequence alignment; Multiple-nucleotide polymorphisms; NCBI; NGS; Network biology; Next-generation sequencing