Applications of machine learning techniques in biology using Weka

(3 customer reviews)

Last day of registration: 29th August, 2022


This product is currently out of stock and unavailable.

SKU: IIT Madras | Dates: September 3th - 4th, 2022 Categories: ,


This workshop aims to provide in-depth knowledge with working examples to utilize machine learning techniques in biological research problems such as classification and real value prediction. A systematic approach for developing an efficient computational tool will be explained in detail with assessment procedures and extensive tutorials. The projects designed in this workshop will help to follow the protocol independently and achieve the goal. The participants of the workshop will be capable of developing reliable bioinformatics tools upon successful completion of the program.

Mode of workshop: Online

Day 1

Module 1: Development of Algorithm

Timings: 10:00 am – 11:30 am

Concepts Covered: 

  • Datasets/features/methods/evaluation
Learning outcome:
  • Efficiently and systematically approaching a bioinformatics problem

Module 2: An Introduction to Weka Machine Learning Workbench

Timings: 11:30 am – 1pm

Concepts Covered: 

Machine learning techniques/input features/interpretation of output

Learning outcome:

Features available in Weka and details on input and output files

Module 3: Live Demo

Timings: 2 pm – 4 pm

Concepts Covered:

Working example

Learning outcome:

Learn methods and validation procedures in WEKA

Live session: 5 hrs 

Day 2

Project 1:

Distinguishing two sets of data

Timings: 10:00 am – 1 pm

Project 2:

Predicting real values

Timings: 2 pm – 4 pm

Learning outcome:
  • Reliable methods and interpretations for prediction
Live session: 5 hrs 

Session dates: 3rd – 4th September, 2022

Time: 3rd September 10am – 1pm, 2pm-4pm

             4th September 10am – 1pm, 2pm-4pm

Last date of Registration: August 29th, 2022

Profile of the Instructor(s)

Prof. M Michael Gromiha received his Ph.D from Bharathidasan University, India and served as STA fellow, RIKEN Researcher, Research Scientist and Senior Scientist at Computational Biology Research Center, AIST, Japan till 2010. Currently, he is working as a Professor at Indian Institute of Technology (IIT) Madras, India. He is teaching courses on bioinformatics, protein structure and function, protein interactions: computational techniques and handling computational biology lab. His main research interests are computational studies on protein structure and function, mutational analysis, machine learning techniques and development of databases and algorithms. He has published over 300 research articles/reviews, 10 editorials and two books on Protein Bioinformatics (Elsevier/Academic Press) and Protein interactions (World Scientific). His papers received about 13,000 citations and his h-index is 60. 

He has received several awards including Institute Research and Development Award, Tamil Nadu Scientist Award, ASC Masila Vijay Award for excellence in scientific research and publications. He is serving as Associate Editor/Editorial Board Member in 10 internationally reputed journals. He is ranked as the topmost 0.5% of researchers in Bioinformatics/Biophysics/overall in the world.


Eligibility & Fees

Basic qualification of participants:

Basic knowledge in programming would be beneficial, but not mandatory

Eligibility criteria: 

BSc/BTech etc. (pursuing/ completed) MSc/MTech; PhD

Fees breakup for the workshop:
  • Students(UG/PG) : 500 +18% GST =  Rs.590
  • Research scholars (PhD): 1000 +18% GST =  Rs.1180
  • Faculty : 2000 +18% GST = Rs.2360
  • Industry: 3000 +18% GST = Rs.3540


After attending all the sessions and submitting assessments and projects, we will provide you with a workshop completion certificate from NPTEL.

3 reviews for Applications of machine learning techniques in biology using Weka

  1. Pooja Rathod (verified owner)

    i learnt new things

  2. BrijeshKumar Arvindbhai Patel (verified owner)

    Workshop was really good and insightful

  3. Tamajit Sadhukhan (verified owner)

    I learn new area of machine learning

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