[bioundgrd] Fall dates, lab requirements, UROPs, new quantitative biology subjects

[Janice Chang]

Dear course 7, 5-7, 6-7 students, biology faculty,

Greetings to everyone.  

FALL 2020
Friday, Aug 14		Pre-registration ends
Monday, Aug 24	Registration opens
Monday, Aug 31	Registration Day
Tues, Sept 1		First day of classes*
Mon, Sept 7		Labor Day
Friday, Oct 2		Add Date
Mon, Oct 12		Columbus Day 
Wed, Nov 11		Veteran’s Day
Wed, Nov 18		Drop date
Sat Nov 21		Thanksgiving break begins^
Sun, Nov 29		Thanksgiving break ends
Wed, Dec 9		Last day of classes
Mon Dec 14		First day of final exams (all remote)
Friday, Dec 18		Last day of final exams (all remote)

*All MIT instruction will be delivered remotely during the first week of classes.  Biology classes in the fall, except for labs, will be offered on-line.
^Students will not return after Thanksgiving break and instruction will be remote through the last day of classes on December 9.


Biology lab requirements
7.002 Fundamentals of Experimental Molecular Biology and 7.003 Applied Molecular Biology Laboratory will be offered in-person in the fall.
Seniors who are not allowed on campus and need to complete 7.002/7.003 in the fall should contact the Biology education office (jdchang at mit.edu <mailto:jdchang at mit.edu>)


UROPS
UROP site:  https://urop.mit.edu <https://urop.mit.edu/>
Students living on campus can do in-person UROPs.  For those off campus, remote UROPs are possible. Contact faculty members to arrange UROPs.


New restricted elective spring courses 7.093 and 7.094 replace 7.09
The department is offering two new quantitative biology half semester subjects that replace 7.09 Quantitative and Computational Biology.

7.093 and 7.094 together fulfill the biology restricted elective requirement.
7.093/7.573 Modern Biostatistics

2-0-4 Spring H3. Prereq: 7.03 and 7.05 

Description: Introduction to probability and statistics used in modern biology. Discrete and continuous probability distributions, statistical modeling, hypothesis testing, Bayesian statistics, independence, conditional probability, Markov chains, methods for data visualization, clustering, principal components analysis, nonparametric methods, Monte Carlo simulations, false discovery rate. Applications to DNA, RNA, and protein sequence analysis, genetics, genomics. Homeworks will involve the R programming language, but prior programming experience is not required. Students registered for the graduate version do an additional project, applying biostatistical methods to data from their research. (C. Burge, A. Jain)


7.094/7.574 Modern Computational Biology
2-0-4 Spring H4. Prereq: 7.03 and 7.05 

Introduction to modern methods in computational biology, focusing on DNA/RNA/protein sequence analysis. Topics coved include next-gen DNA sequencing and sequencing data analysis, RNA-seq (bulk and single-cell), ribosome profiling, and proteomics. Students registered for the graduate version do an additional project, applying bioinformatic methods to data from their research.  (A. Jain, G.W. Li)



Best wishes and take care.


 
Sincerely,
Janice


***********************
Janice Chang | Educational Administrator | Department of Biology | MIT
rm:68-120 | ph: 617.253.7344 | jdchang at mit.edu





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