Course

Unit 1

Introduction to Machine Learning

Overview of intelligent systems and machine learning – Knowledge Discovery process – Data understanding and Data exploration – Data Preprocessing

Unit 2

Supervised Learning

Supervised Learning: Classification introduction, performance evaluation, a first simple classifier: Decision tree – Rule-based algorithms – Linear regression – Logistic regression – Advanced Classification methods: Random Forest, Support Vector Machine, Neural Networks

Unit 3

Unsupervised Learning

Unsupervised learning: Clustering: K-Means clustering, DBSCAN – Hierarchical clustering – Pattern mining: a-priori pattern mining

Unit 4

Application of Deep Learning in Bioinformatics

Supervised Learning: Deep Learning with Recurrent Neural Networks: architecture – Protein structure/function prediction using machine learning – application of graph neural network for the prediction of protein interaction network – Deep learning applications to genomics :DNA motif discovery – Deep learning applications to genomics: single cell RNAseq analysis and interpretation

Unit 5

Deep Learning Case Study Bioinformatics

Define Project Objective – Acquire & Explore Data – Model Building – Model validation – Interpret & Communicate – Data Visualization

LEARNING OBJECTIVES:

The objective of this course is to understand the commonly used machine learning algorithms and provide insight into their theoretical foundations. This course has a special focus on machine learning algorithms for analyzing biological data such as protein/DNA sequences, protein structures, molecular graphs, and so on.

COURSE OUTCOMES:

After completing the course, students shall be able to

CO 1. Different types of machine learning and its utility in bioinformatics

CO 2. Application of Hidden Markov Model and Artificial neural networks to different types of bioinformatics data

CO 3.  Determination of Bayesian Network (BN) from expression data.

1. A Silberschatz, H.F. Korth & S. Sudarshan: Data Base System Concepts, TMH, 1997.
2. K. Majumdar and Bhattacharyya: Database Management Systems, THM, 1996.
3. J. Date: An Introduction to Database systems 7th Ed. Addison Wesley, Indian Edition, 2000.
4. Elmasri & Navathe : Fundamentals of Database Systems/Oracle 9i Programming 5th Ed. Pearson, 2009