This is a skill oriented course to provide hands-on practice and project work in the computational biological study involving different in silico techniques, including database mining, data retrieval, data curation, annotation, and structural characterization.
Introduction to Computational Biology
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Code(Credit) : CUTM3108 (0-3-1)
| Scheme | Skill for Success (SFS) |
| NSQF Level | 4 |
| Duration | 4 Months |
| Sector | Skill Council for Green Jobs (SCGJ) |
| Occupations | Sequence Analysis |
| Entry Qualification | Diploma/B. Tech/Applied Science/ Agriculture |
| Minimum Age | 18 Years |
| Aligned to (QP) | |
Course Objectives:
The objectives of this subject are:
To foster the students with in silico bioinformatics education for their future career.
- To learn the basic concepts of Bioinformatics and its significance in Biological data analysis.
- To inculcate the advanced tools and databases of genomics and its applications.
- To obtain the hands-on-training in in silico basics related to functional genomics.
- Can join industry as a Sequence analyst or Bioinformaticianand will progress.
- Can become entrepreneur in the related field.
- Can do Diploma or any Advance program in the same.
Industry Participation:
- Department of Biotechnology, Phytopharma Lab, CUTM, Odisha.
- BIOVIA.
Course Syllabus/Contents:
Module 1:
Unit 1: History, Scope and Importance, Databases- Tools and their Uses,
Unit 2: Introduction to various tools and databases - DNA Databases - NCBI and its GenBank resources, KEGG and its resources, DNA Data Bank of Japan (DDBJ).
Unit 3: National Centre for Biotechnology Information (NCBI): cDNA libraries and Expressed Sequence Tags (ESTs), EST analysis, Pairwise alignment techniques, Multiple sequence alignment.
Unit 4: Kyoto Encyclopedia of Genes and Genomes (KEGG): Modules, Network, Genomes, Genes and KEGG analysis tools.
Unit 5: DNA Data Bank of Japan (DDBJ): Sequence Alignment Methods, Predictive Methods Using DNA Sequences.
Module 2:
Unit 1: Protein Information Resources (PIR)
Unit 2: SWISS PROT and Protein Data Bank (PDB): Protein features and motifs, annotation and curation, protein structure analysis.
Module 3:
Unit 1: Phylogenetic analysis: Evolution, elements of phylogeny, methods of phylogenetic analysis, Phylogenetic tree of life, comparison of genetic sequence of organisms, phylogenetic analysis tools-Phylip, ClustalW.
Unit 2: BLAST: Basic Local Alignment Search Tool: Nucleotide BLAST, Protein BLAST, Blastn, Blastp, Blastx, tBlastn, tBlastx
Unit 3: Sequence Alignment: MSA using conserved domain and local sequence similarity information, COBALT, Protein sequence alignment, Nucleotide sequence alignment.
Module 4:
Applications of bioinformatics tools in Agriculture, Medicine, Diary, Health Industry, Environment, Biotechnology, Genomics, Transcriptomics and Proteomics; Bioinformatics and Career.
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Dr. Pushpalatha G., Professor, Department of Plant Biotechnology, Centurion University of Technology and Management, Odisha has many accomplishments. As a Principle Investigator (PI), she runs a project entitled ‘Genome-wide haplotype analysis for salt tolerance associated candidate genes in rice’ funded by SERB (TAR/2021/000258 dated 2nd December 2021), Government of India, India. She is also a […]
