Course

Unit 1

Unit 1:

Introduction to Bioinformatics and Molecular Diagnostics, Overview of bioinformatics and its relevance in healthcare, Basic concepts in molecular diagnostics, Key biomolecules: DNA, RNA, and proteins, Bioinformatics pipeline in diagnostic workflows, Ethical considerations and data privacy, Learning Activities: Case studies, introductory tutorials.

Unit 2

Unit 2:

Biological Databases and Data Retrieval, Types of biological databases: primary, secondary, specialized, Genomic and proteomic data repositories (GenBank, Ensembl, UniProt, ClinVar), Data formats (FASTA, FASTQ, VCF, GTF), Database querying and data interpretation.

Unit 3

Unit 3:

Sequence Alignment and Similarity Search, Principles of sequence alignment: local vs. global, Algorithms: Needleman-Wunsch, Smith-Waterman, BLAST, Multiple sequence alignment (MSA) and applications, Interpretation of alignment scores in diagnostics.

Unit 4

Unit 4:

Gene Annotation and Functional Prediction, Gene structure and annotation pipelines, Identification of coding regions and regulatory elements, Functional annotation using ontologies (GO, KEGG), Gene-disease associations.

Unit 5

Unit 5:

Variant Analysis and Interpretation, Types of genetic variants and their clinical significance, Variant calling workflows and quality control, Databases for variant interpretation (dbSNP, ClinVar, COSMIC), Pathogenicity prediction tools.

Unit 6

Unit 6:

Data Visualization and Reporting in Diagnostics, Visualization of genomic and proteomic data, Integrative genome viewers and heatmaps, Creating diagnostic reports, Translating bioinformatics findings into clinical insights.

(45 classes)

Preamble

This course introduces students to the application of bioinformatics in the field of molecular diagnostics. It covers databases, algorithms, and computational tools used to analyze genomic and proteomic data for disease diagnosis and monitoring. Students will explore sequence alignment, gene annotation, variant analysis, and data visualization in a diagnostic context.

Course outcomes

CO1: To understand bioinformatics’ role in diagnostics, including ethical issues and data privacy.

CO2: To use biological databases and interpret genomic/proteomic data formats.

CO3: To apply sequence alignment techniques and algorithms for diagnostics.

CO4: To annotate genes and predict their functions using gene-disease associations.

CO5: To analyze genetic variants and assess pathogenicity using variant databases.

CO6: To visualize genomic data and create diagnostic reports.

Program outcome

PO1: Bioscience Knowledge

PO2: Problem Analysis

PO3: Design/Development of Solutions

PO4: Conduct Investigations of complex problems

PO5: Modern tools usage

PO6: Bioscientist and Society

PO7: Environment and Sustainability

PO8: Ethics

PO9: Individual & Team work

PO10: Communication

PO11: Project management & Finance

PO12: Lifelong learning

0 – No affinity; 1 – low affinity; 2 – Medium affinity; 3 – High affinity

Program-specific outcome

PSO 1 – Emerging technologies in clinical diagnostics

PSO 2 – Biomolecules in Medicine

PSO 3 – Molecular dysregulation in diseases

PSO 4 – Molecular technology in diagnosis and therapy

PSO 5 – Applying lab discoveries to clinical practice

PSO 6 – Microorganisms in Medicine

PSO 7 – Statistical methods to interpret and validate diagnostic results

PSO 8 – Integrate molecular diagnostics into personalized medicine

PSO 9 – Compounds as biomarkers and its specificity

PSO 10 – Bioinformatics and biological data use

0 – No affinity; 1 – low affinity; 2 – Medium affinity; 3 – High affinity

Textbook:

Pevsner J. Bioinformatics and Functional Genomics. 3rd ed. Hoboken (NJ): Wiley-Blackwell; 2015.

Reference Book:

Mount DW. Bioinformatics: Sequence and Genome Analysis. 2nd ed. Cold Spring Harbor (NY): Cold Spring Harbor Laboratory Press; 2004.