Lecture/Recitation Topic SMA 5303 L1 Sampling and statistical distributions
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1 SMA 50: Statistical Learning and Data Mining in Bioinformatics (also listed as 5.077: Statistical Learning and Data Mining ()) Spring Term (Feb May 200) Faculty: Professor Roy Welsch Wed 0 Feb 7:00-8:0 PM Mon 08 Feb 7:00-8:0 PM Wed 0 Feb 7:00-8:0 PM Thurs 04 Feb Tues 09 Feb Thurs Feb SMA 50 L Sampling and statistical distributions Homework # handed out SMA 50 L2 Estimation, confidence intervals, and the bootstrap SMA 50 L Hypothesis testing, likelihood ratios, goodness-of-fit tests, approximate methods Accurate as of Jan 27, 200 NTU References R 6, 7.-7., R 8., , 8.7, 8.9, R , 8.2, Tues 9 Feb Thurs Feb 0:0-:0 AM * Rec.: Computing: graphics and the bootstrap R 9.8, 0.2., 0., NO CLASS ---- Singapore Holiday Chinese New Year from 4 Feb to 6 Feb 200 NO CLASS - holiday Presidents Day on 5 Feb 200 Tues 6 Feb 7:00-8:0 PM Wed 7 Feb SMA 50 L4 Bayesian inference, Molecular biology fundamentals Roy Welsch ( Monday schedule of classes to be held) Jagath Rajapakse R.5.2 (94,95), 8.6, BB 2.-2., CB.0-.7 Wed 7 Feb 7:00-8:0 PM Thur 8 Feb 7 Thurs 8 Feb Thurs 8 Feb 0:0-:0 AM SMA 50 L5 Die models of sequences, Markov models, pairwise sequence alignment Tentative homework # due dates Homework # 2 handed out Rec.: Testing and Bayesian Inference BB.; EG , , *:. Live video-casting from ; 2. Taped lecture from ;. Live video-casting from S pore; 4. Taped lecture from S pore; 5. Classroom lecture in S pore; 6. faculty teaches in S pore; 7. Recitation by faculty to students at and by NTU faculty to students at Singapore; 8. Other-Please specify
2 SMA 50: Statistical Learning and Data Mining in Bioinformatics (also listed as 5.077: Statistical Learning and Data Mining ()) Spring Term (Feb May 200) Faculty: Professor Roy Welsch Mon 22 Feb 7:00-8:0 PM Wed 24 Feb 7:00-8:0 PM Tues 2 Feb Thurs 25 Feb 7 Tues 2 Feb Thurs 25 Feb 0:0-:0 AM Mon 0 Mar 7:00-8:0 PM Wed 0 Mar 7:00-8:0PM Tues 02 Mar Thurs 04 Mar 7 Tues 02 Mar Thurs 04 Mar 0:0-:0 AM Mon 08 Mar 7:00-8:0PM Wed 0 Mar 7:00-8:0PM Tues 09 Mar Thurs Mar SMA 50 L6 Substitution matrices, multiple sequence alignment, Markov chain Monte Carlo, simulated annealing, Gibbs sampling, BLAST SMA 50 L7 Hidden Markov models: gene structure prediction, profile HMM, Expectation- Accurate as of Jan 27, 200 NTU References EG , ,.-.7 Brooks paper BB EG Maximization algorithm Rec.: Die models; Markov modeling BB. EG ,.-.4 SMA 50 L8 Linear regression and smoothing SMA 50 L9 Regression diagnostics, collinearity, and robust regression Tentative homework # 2 due dates Homework # handed out Rec.: Computing: regression and Gene structure prediction with HMM SMA 50 L0 Comparing two samples; non-parametric methods and experimental design SMA 50 L Analysis of categorical data R4.4.2, , 4.7 Notes, R , 4.8 R.-.5 R., Tues 09 Mar Thurs Mar 0:0-:0 AM Rec.: Computing: diagnostics and twosample *:. Live video-casting from ; 2. Taped lecture from ;. Live video-casting from S pore; 4. Taped lecture from S pore; 5. Classroom lecture in S pore; 6. faculty teaches in S pore; 7. Recitation by faculty to students at and by NTU faculty to students at Singapore; 8. Other-Please specify
3 SMA 50: Statistical Learning and Data Mining in Bioinformatics (also listed as 5.077: Statistical Learning and Data Mining ()) Spring Term (Feb May 200) Faculty: Professor Roy Welsch NTU Accurate as of Jan 27, 200 References Daylight Savings Time Start Note Time Change at NTU and (starts from 4 March 09-2 hours difference) Mon 5 Mar Tues 6 Mar 7 Tues 6 Mar 0:0-:0 AM 8 (no beaming) Wed 7 Mar Thurs 8 Mar SMA 50 L2 Analysis of variance Tentative homework # due dates Rec.: Categorical Data and ANOVA Midterm Examination (in-class) R Spring Vacation March, (Mon Sun) Mon 29 Mar Wed Mar Tues 0 Mar Thurs 0 Apr 7 Tues 0 Mar Thurs 0 Apr 0:0-:0 AM Mon 05 Apr Tues 06 Apr SMA 50 L4 Learning from data Homework # 4 handed out SMA 50 L5 Model Assessment Rec.: Insightful Miner Basics SMA 50 L6 Regression Selection: Ridge, PCR, PLS, LAR H, 2 H7.-7.7, H.-.6,.9 Wed 07 Apr Thurs 08 Apr SMA 50 L7 Discriminant Analysis; Logistic Regression Tentative homework # 4 due dates Homework # 5 handed out H *:. Live video-casting from ; 2. Taped lecture from ;. Live video-casting from S pore; 4. Taped lecture from S pore; 5. Classroom lecture in S pore; 6. faculty teaches in S pore; 7. Recitation by faculty to students at and by NTU faculty to students at Singapore; 8. Other-Please specify
4 SMA 50: Statistical Learning and Data Mining in Bioinformatics (also listed as 5.077: Statistical Learning and Data Mining ()) Spring Term (Feb May 200) Faculty: Professor Roy Welsch 7 Tues 06 Apr Thurs 08 Apr 0:0-:0 AM Mon 2 Apr Wed 4 Apr Tues Apr Thurs 5 Apr 7 Tues Apr Thurs 5 Apr 0:0-:0 AM Rec.: Regression Selection SMA 50 L8 Generalized Additive Models and Trees: CART SMA 50 L9 Support Vector Machines; Support Vector Regression; Prediction of protein features: secondary structures, solvent accessibility, and accessibility area Rec.: Classification, logistics Reg., and SVM NTU Accurate as of Jan 27, 200 References H H4.5, 2.-2., (omit 2.., 2..5) Nguyen & Rajapakse 2005, 2006, 2007 holiday Patriots Day, 9-20 Apr (Mon, Tues) No Class Wed 2 Apr Thurs 22 Apr SMA 50 L20 Neural Networks, prediction of signal sites in genomic sequences H.,.-.0 Rajapakse & Ho 2005 Mon 26 Apr Tues 27 Apr SMA 50 L2 Cluster analysis, k-means, hierarchical clustering, clustering of gene expressions, biclustering H.-.2, 4. (omit 4..9) Wed 28 Apr Thurs 29 Apr Tentative homework # 5 due dates Homework # 6 handed out SMA 50 L22 Bagging and Boosting, AdaBoost, Random Forests H , , *:. Live video-casting from ; 2. Taped lecture from ;. Live video-casting from S pore; 4. Taped lecture from S pore; 5. Classroom lecture in S pore; 6. faculty teaches in S pore; 7. Recitation by faculty to students at and by NTU faculty to students at Singapore; 8. Other-Please specify
5 SMA 50: Statistical Learning and Data Mining in Bioinformatics (also listed as 5.077: Statistical Learning and Data Mining ()) Spring Term (Feb May 200) Faculty: Professor Roy Welsch 7 Tue 27 April Thurs 29 Apr 0:0 -:0AM 7 Mon 0 May Tues 04 May 9:00 :00 AM Rec.: Neural Nets, CART, Bagging and Boosting SMA 50 L2 Project consultation NTU Accurate as of Jan 27, 200 References 7 Wed 05 May Thurs 06 May 9:00 :00 AM Tues 04 May Thurs 06 May 7 :00AM -2:00 PM 7 Mon 0 May Tues May 9:00-:00 AM 7 Tues May Tues May :00 AM -2:00PM 7 Wed 2 May Thurs May 9:00 :00 AM SMA 50 L24 Project consultation Tentative homework # 6 due dates Rec.: Clustering and Neural Nets SMA 50 L25 Project presentations Rec.: Project help SMA 50 L26 Project presentations Project report due Texts:. John A. Rice, Mathematical Statistics and Data Analysis (Third Edition, 2007) [R] An alternative to Rice, especially if you are interested in bioinformatics might be: 2. Warren J. Ewens, Gregory R. Grant, Statistical Methods in Bioinformatics: An Introduction, Second Edition [EG]. Hastie, Tibshirani, and Friedman, The Elements of Statistical Leaning: Data Mining, Inference, and Prediction [H] On reserve or portions handed out: *:. Live video-casting from ; 2. Taped lecture from ;. Live video-casting from S pore; 4. Taped lecture from S pore; 5. Classroom lecture in S pore; 6. faculty teaches in S pore; 7. Recitation by faculty to students at and by NTU faculty to students at Singapore; 8. Other-Please specify
6 SMA 50: Statistical Learning and Data Mining in Bioinformatics (also listed as 5.077: Statistical Learning and Data Mining ()) Spring Term (Feb May 200) Faculty: Professor Roy Welsch 4. P. Baldi and S. Brunak, Bioinformatics: The Machine Learning Approach, Second Edition [BB] Accurate as of Jan 27, P. Clote and R. Backofen, Computational Molecular Biology: An Introduction [CB] 6. R. Durbin, S. Eddy, A. Krogh, and G. Mitchison, Biological Sequence Analysis: Probabilistic Models of Proteins and Nucleic Acid [DEKM] *Note that lab sessions are held at SCE Multi-Media Lab at N4-0A-02 *:. Live video-casting from ; 2. Taped lecture from ;. Live video-casting from S pore; 4. Taped lecture from S pore; 5. Classroom lecture in S pore; 6. faculty teaches in S pore; 7. Recitation by faculty to students at and by NTU faculty to students at Singapore; 8. Other-Please specify
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