CSCI4969-6969 Machine Learning in Bioinformatics
This course focuses on machine learning algorithms for analyzing biological data. The course will introduce the main topics in this area, such as analysis of protein/DNA sequences, protein structures, molecular graphs, and so on. The main focus is on the role of deep learning and data mining in computational biology and bioinformatics.
Class Hours: 10-11:50AM MR, Carnegie 201. Office Hours: 12-1PM MR
Online Class: https://rensselaer.webex.com/meet/zakim
Syllabus: CSCI4969-6969 Syllabus
Campuswire: https://campuswire.com/c/G8B78468D
Submitty: https://submitty.cs.rpi.edu/courses/s22/csci4969
Assignments
Capstone2: CSCI4969-6969 Capstone2 , Due: 25th Apr
Capstone1: CSCI4969-6969 Capstone1 , Due: 19th Apr
Assign6: CSCI4969-6969 Assign6 , Due: 7th Apr
Assign5: CSCI4949-6969 Assign5, Due: 25th Mar
Assign4: CSCI4949-6969 Assign4, Due: 6th Mar
Assign3: CSCI4949-6969 Assign3, Due: 22nd Feb
Assign2: CSCI4969-6969 Assign2, Due: 9th Feb
Assign1: CSCI4969-6969 Assign1, Due: 1st Feb
Assign0: CSCI4969-6969 Assign0, Due: 13th Jan
Class schedule
Tentative course schedule is given below.
Date | Topic | Lectures | Readings |
---|---|---|---|
Jan 10 | Introduction I | intro.pdf, lecture1 video | Intro to Molecular Biology (on LMS) |
Jan 13 | Introduction II | intro.pdf, lecture2 video | |
Jan 17 | NO CLASS (MLK, Jr. Day) | ||
Jan 20 | Neural Networks (MLPs) | lecture3.pdf, lecture3 video | |
Jan 24 | MLPs II | lecture4.pdf, lecture4 video | |
Jan 27 | RNNs | lecture5.pdf, lecture5 video | |
Jan 31 | RNNs, LSTMs | lecture6.pdf, lecture6 video | |
Feb 03 | CNNs | lecture7.pdf, lecture7 video | |
Feb 07 | Word Embeddings | lecture8.pdf, lecture8 video | |
Feb 10 | Attention | lecture9.pdf, lecture9 video | |
Feb 14 | Transformer | lecture10.pdf, lecture10 video | |
Feb 17 | Language Models (BERT) | lecture11.pdf, lecture11 video | |
Feb 22(T) | Graph Neural Networks (GNNs) | lecture12.pdf, lecture12 video | |
Feb 24 | GNN IIs | lecture13.pdf, lecture13 video | |
Feb 28 | BERT for Proteins | lecture14.pdf, lecture14 video | |
Mar 03 | GNNs III | lecture15.pdf, lecture15 video | |
Mar 07 | NO CLASS (Spring Break) | ||
Mar 10 | NO CLASS (Spring Break) | ||
Mar 14 | Pytorch Implementation Tips | lecture16.pdf, lecture16 video | |
Mar 17 | GNN Assignment & Protein Structure | lecture17.pdf, lecture17 video | |
Mar 21 | Protein Structure Prediction | lecture18.pdf, lecture18 video | |
Mar 24 | AlphaFold1 I | lecture19.pdf, lecture19 video | |
Mar 28 | NO CLASS | ||
Mar 31 | Alphafold1 II | lecture20.pdf, lecture20 video | |
Apr 04 | Alphafold1 III | lecture21.pdf, lecture21 video | |
Apr 07 | Alphafold2 I | lecture22.pdf, lecture22 video | |
Apr 11 | Alpahafold2: Evoformer | lecture23.pdf, lecture23 video | |
Apr 14 | Alphafold2: Evoformer II | lecture24.pdf, lecture24 video | |
Apr 18 | Alphafold2: Structure Prediction I | lecture25.pdf, lecture25 video | |
Apr 21 | Alphafold2: Structure Prediction II | lecture26.pdf, lecture26 video | |
Apr 25 | Wrap Up | lecture27.pdf, lecture27 video |