Artificial Intelligence in Bioinformatics

UG Course Scheme

1. M.Tech (Artificial Intelligence) R2019 [ Scheme ]

2. MEAIDLO2021 Artificial Intelligence in Bioinformatics [ Syllabus ]

3. Question Bank Booklet QBB - Jan 2025 [ PDF ] [ SpreaSpreadsheet ]

Course Outcomes 

Upon completion of the course, the learners will be able to:

1. Understand the concepts of molecular biology, DNA analysis with respect to data processing.

2. Analyze biological sequences and score matrices with respect to data processing.

3. Implement data mining algorithms on microarray, gene expression, feature selection for proteomic and genomic data.

4. Understand ethics in using bioinformatics.

5. Apply AI in medical field for development of contributive solutions.

6. Investigate state-of-the-art research and developments in bioinformatics.

Course Materials (PPTs/PDFs/Handouts)

• • Module 1: Introduction

    • Introduction to Bioinformatics  [ PDF ]

    • Introduction to Data Mining [ PDF ]

  • Module 2: Biological Sequence Analysis

    • Biological Sequence Analysis [ PDF ]

  • Module 3: Mining Biological Data

    • Introduction [ PDF ]

  • Module 4: Ethics in Bioinformatics

    • Ethics  [ PDF ]

  • Module 5: AI in Medical Informatics

    • AI in Medical Informatics [ PDF ]

  • Module 6: Case Studies

    • Case Studies [ PDF ]

Course Examination and Evaluation

• 2024-25

  • MTech AI Sem-II MU QP dated 2024-07 [ PDF ]

• 2023-24

  • Internal Assessment #1: [ PDF ]  [ Solution PDF ]

  • Internal Assessment #2: [ IA1 QP PDF ]  [ IA1 Solution PDF ]

  • Assignment #1 : [ Assign1 Question PDF ]       [ Assign1 Solution PDF ] 

  • Assignment #2:  [ Assign2 Question ]      [ Assign2 Solution ]  

  • Practice Quiz #1 [ Google Form ]

  • Theory Examination [ QP PDF ]   [ TH QP Solution PDF ]

• 2022-23

Lab Experiments

• Guidelines for writing Lab Experiments [ PDF ]

• Module 1: Introduction

  • Lab 1: [ PDF ]

  • Lab 2: [ PDF ]

  • Lab 3: [ PDF ]

• Module 2: Biological Sequence Analysis

  • Lab 4: [ PDF ]

  • Lab 5: [ PDF ]

• Module 3: Mining Biological Data

• Lab 6: [ PDF ]

• Lab 7:  [ PDF ]

• Module 4: Ethics in Bioinformatics

  • Lab 8: [ Lab8.ipynb ]

  • Lab 9: [ Lab9.ipynb ]

• Module 5: AI in Medical Informatics

  • Lab 10: 

• Module 6: Case Studies

  • Lab 11: 

Lab Manual

• Lab Manual [ PDF ]