Home of the Uedu platform

UeduGPTs

--

Jupyters

15

Local AI

--

Uedu Code

--

CISOSE26 Local AI Uedu Code UG26

AI Reply Desktop Notifications

Show a desktop notification when the AI TA finishes replying

Chat Message Notifications

Notify me when classmates post messages in the forum

Sound notification

Play an alert sound whenever there is a new notification

More settings

Account settings Data privacy settings Research Informed Consent Form

7.91J

Foundations of Computational and Systems Biology

Prof. Christopher Burge, Prof. David Gifford, Prof. Ernest Fraenkel | Spring 2014

Science & Math Biology Engineering Biological Engineering Systems Engineering Computation and Systems Biology Computational Biology Computational Modeling and Simulation

Go to original course

CC BY-NC-SA 4.0

Course introduction

This course is an introduction to computational biology emphasizing the fundamentals of nucleic acid and protein sequence and structural analysis; it also includes an introduction to the analysis of complex biological systems. Topics covered in the course include principles and methods used for sequence alignment, motif finding, structural modeling, structure prediction and network modeling, as well as currently emerging research areas.

Course Information

Source	MIT 開放式課程
Department	Biological Engineering
Language	English
Number of videos	22

Course videos (22)

1. Introduction to Computational and Systems Biology

1. Introduction to Computational and Systems Biology

2. Local Alignment (BLAST) and Statistics

2. Local Alignment (BLAST) and Statistics

3. Global Alignment of Protein Sequences (NW, SW, PAM, BLOSUM)

3. Global Alignment of Protein Sequences (NW, SW, PAM, BLOSUM)

4. Comparative Genomic Analysis of Gene Regulation

4. Comparative Genomic Analysis of Gene Regulation

5. Library Complexity and Short Read Alignment (Mapping)

5. Library Complexity and Short Read Alignment (Mapping)

6. Genome Assembly

6. Genome Assembly

7. ChIP-seq Analysis; DNA-protein Interactions

7. ChIP-seq Analysis; DNA-protein Interactions

8. RNA-sequence Analysis: Expression, Isoforms

8. RNA-sequence Analysis: Expression, Isoforms

9. Modeling and Discovery of Sequence Motifs

9. Modeling and Discovery of Sequence Motifs

10. Markov and Hidden Markov Models of Genomic and Protein Features

10. Markov and Hidden Markov Models of Genomic and Protein Features

11. RNA Secondary Structure; Biological Functions and Predictions

11. RNA Secondary Structure; Biological Functions and Predictions

12. Introduction to Protein Structure; Structure Comparison and Classification

12. Introduction to Protein Structure; Structure Comparison and Classification

13. Predicting Protein Structure

13. Predicting Protein Structure

14. Predicting Protein Interactions

14. Predicting Protein Interactions

15. Gene Regulatory Networks

15. Gene Regulatory Networks

16. Protein Interaction Networks

16. Protein Interaction Networks

17. Logic Modeling of Cell Signaling Networks

17. Logic Modeling of Cell Signaling Networks

18. Analysis of Chromatin Structure

18. Analysis of Chromatin Structure

19. Discovering Quantitative Trait Loci (QTLs)

19. Discovering Quantitative Trait Loci (QTLs)

20. Human Genetics, SNPs, and Genome Wide Associate Studies

20. Human Genetics, SNPs, and Genome Wide Associate Studies

21. Synthetic Biology: From Parts to Modules to Therapeutic Systems

21. Synthetic Biology: From Parts to Modules to Therapeutic Systems

22. Causality, Natural Computing, and Engineering Genomes

22. Causality, Natural Computing, and Engineering Genomes