CS374 - Algorithms in Biology

Course Description

This course will cover algorithms and computational models applied to molecular biology. Current, exciting algorithms from a variety of biological areas will be covered. The topics should be of interest to computer scientists and biologists alike. We will cover topics from genomics and evolution of DNA, such as current sequence analysis methods, regulatory programs, speciation and selection, to the applications of computational biology to the study of diseases. We will also cover topics in structural biology (RNA and protein structure), systems biology, imaging, the use of computational methods in metabolic engineering and biological computation. The course will consist primarily of student presentations of topics in the syllabus, which will be prepared with the help of the instructor. Students will help forming the syllabus, by choosing the topics they would like to present.

Class Schedule

Lecture: Tue Thu 11:00am-12:15pm, Y2E2 building, room 111

Instructor

Serafim Batzoglou
Office: Clark Center S266
Office hours: TBA.
Meeting before your presentation: By appointment.
Phone: (650) 723-3334
Email: ude.drofnats@mifares (written backwards to avoid spam)

Teaching Assistant

Marc A. Schaub
Office: Clark Center S260
Office hours: Monday 2pm-4pm, Wednesday 2pm-4pm
Paper discussion: by appointment.
Phone: (650) 725-6094
Email:

Prerequisites

The following courses are recommended:

CS161: Design and Analysis of Algorithms, or equivalent familiarity with algorithmic and data structure concepts.
CS262: Computational Genomics, or CS274: Representations and Algorithms for Computational Molecular Biology, or BIOCHEM218: Computational Molecular Biology, or equivalent familiarity with computational biology concepts, problems and algorithms.

Course Requirements

There are four course requirements:

Presentation. The main course requirement is to select a topic and give a presentation based on two papers on the topic. The instructor and TA will meet with each student to help with the preparation, and ensure that the resulting presentation will be interesting and accessible to students in the class who are not experts in the given topic. Most of the topics have a strong algorithmic flavor, but some topics are more geared towards biology. Please send the slides in powerpoint (.ppt,.pptx) or PDF format to the TA on the day of your presentation.
Critique. The second requirement is the critique of one of the papers that will be presented in lecture. The critique has to be written and submitted before the topic is presented in class. You will be assigned one class for the critique. You should choose one of the papers that will be presented during that class, read and understand the paper, and then write a critique. The critique should be 2 to 3 pages long (using a 12pt font and standard page setup). The critique must be submitted before class (ie. before 11am on the assigned day) by emailing a PDF file to the TA. Submissions received during or after class will not be considered. You are required to attend the class during which the paper you critiqued is presented, and are strongly encouraged to share your comments about the paper in the discussion. You may be asked to perform some editing (if necessary) before your critique appears online. The critique should not just be a summary of the paper, but rather demonstrate critical thinking about the content of the paper. Points that can be discussed in the critique include the methodology used in the paper, the quality of the results and their validation, possible shortcomings, alternative approaches to solving the problem, ideas for the extension of the presented approach, and comparisons between the paper and other work in the area. You are encouraged to discuss ideas for your critique with the TA. Keep in mind that your critique constitutes an original text; verbatim copying from any sources is not allowed.
Summary. As a third requirement, you need to select two lectures: one of lectures 3 to 10, and one of lectures 11 to 19 (except lectures 15 and 16). For each lecture, you have to find one paper in addition to the two presented; the paper must be related to the topic and relatively recent (published after 2004). Then, you must write a single-page summary of what the paper presents and how it relates to the other two. Refer to the sample entry for examples of how the summary should look like in terms of format and structure. Each of your two summaries is due one week after its respective lecture, but it may appear online later, as you may be asked to perform some editing (if necessary). The summaries should be submitted by emailing a PDF file to the TA. You do not need to sign up for summaries. If you are not sure if a paper is suitable for a summary, or need other advice, feel free to contact the TAs. Keep in mind that your summaries constitute an original text; verbatim copying from any sources (including the paper you are summarizing) is not allowed.
Attendance. As this is a seminar-style class, attendance is mandatory, and each student can miss up to two classes without affecting his/her grade. You are required to attend the full class period. We will circulate an attendance sheet during each class. If you came late or have to leave early, please mention so on the attendance sheet. It is a Honor Code violation to sign the attendance sheet on behalf of somebody else, or to ask somebody else to sign the attendance sheet if one is not attending the class, or to indicate that you attended the whole class if you missed a part of the class.

If you take the class for two units, you can drop (2) or (3) above; or, in case enrollment is too high we will consider dropping (1) if you prefer.

Getting started...

We are assigning presentation topics, presentation dates and critique dates on a first come-first served basis. Please note that your presentation, critique and summaries all need to be on distinct classes (and topics). Critiques are assigned by date, not by topic. To sign up for a presentation, you need to find a topic and a date. Consult the topic list and the schedule, which we will try to update on a rolling basis as soon as assignments are made. As soon as possible, but no later than Friday, April 3, you should send an email with:

A list of at least five topics, in order of preference.
A list of at least five presentation dates, sorted by order of preference.
A list of at least five dates for the critique (unless you are taking the class for two units and want to drop the critique).
Mention if you are taking the class for two or for three units.

Flexibility in terms of possible dates is greatly appreciated. You cannot critique the same day you are presenting, but giving overlapping dates is fine.

Honor Code

The Stanford Honor Code applies to every document you submit for this class. In particular, please be careful not to plagiarize the papers you are presenting or summarizing. Make sure that you always correctly cite your sources (for examples, when you show figures or use illustrations in your presentations). Summaries and critiques must be written using your own words, not by copying text from the respective papers. If you need to cite text verbatim from some source, always put it in quotes and mention the source. If you have any question about this, or in case of doubt, please contact the TAs.

Communication

Questions should be sent to the instructor and the TA directly with email, or communicated to course staff in person after lecture or during office hours.

Topics

The following is a tentative list of topics:

Topic description
	Papers	Assigned to

Sequence Alignment
1	Whole genome alignment Enredo and Pecan: Genome-wide mammalian consistency-based multiple alignment with paralogs Multiple whole-genome alignments without a reference organism Uncertainty in homology inferences: Assessing and improving genomic sequence alignment
2	Topics in sequence alignment PALMA: mRNA to genome alignments using large margin algorithms Probabilistic consistency-based multiple sequence alignment CONTRAlign: discriminative training for protein sequence alignment

Regulatory motif finding
3	Finding regulatory programs Allegro: Analyzing expression and sequence in concert to discover regulatory programs Genome-wide computational prediction of transcriptional regulatory modules reveals new insights into human gene expression Systematic functional characterization of cis-regulatory motifs in human core promoters
4	Approaches to motif finding MotifCut: regulatory motifs finding with maximum density subgraphs Systematic discovery of regulatory motifs in conserved regions of the human genome, including thousands of CTCF insulator sites

Phylogenetic Trees
5	Inference of phylogenetic trees Accurate gene-tree reconstruction by learning gene- and species-specific substitution rates across multiple complete genomes (new) Fast Neighbor Joining	Zinnia Zheng

Chromatin structure
6	Nucleosome Positioning A Genomic Code for Nucleosome Positioning High-throughput mapping of the chromatin structure of human promoters Nucleosome positions predicted through comparative genomics	Gus Katsiapis

Current Trends in Genome Sequencing
7	Sequencing human genomes The diploid genome sequence of an individual human The complete genome of an individual by massively parallel DNA sequencing The diploid genome sequence of an Asian individual
8	Short read assembly ALLPATHS: De novo assembly of whole-genome shotgun microreads Whole-Genome Sequencing and Assembly with High-Throughput, Short-Read Technologies Ab initio Whole Genome Shotgun Assembly with Mated Short Reads
9	Metagenomics Metagenomics: DNA Sequencing of Environmental Samples Environmental Genome Shotgun Sequencing of the Sargasso Sea CompostBin: A DNA composition-based algorithm for binning environmental shotgun reads

RNA Biology
10	RNA secondary structure prediction CONTRAfold: RNA secondary structure prediction without physics-based models A max-margin model for efficient simultaneous alignment and folding of RNA sequences
11	Non-coding RNAs and function Long non-coding RNAs: insights into functions Differentiating Protein-Coding and Noncoding RNA: Challenges and Ambiguities Specific expression of long noncoding RNAs in the mouse brain.
12	MicroRNA detection Most mammalian mRNAs are conserved targets of microRNAs Systematic discovery and characterization of fly microRNAs using 12 Drosophila genomes The role of site accessibility in microRNA target recognition

Structural Biology
13	RNA tertiary structure modeling The MC-Fold and MC-Sym pipeline infers RNA structure from sequence data Coarse-grained modeling of large RNA molecules with knowledge-based potentials and structural filters Automated de novo prediction of native-like RNA tertiary structures
14	Protein folding and molecular dynamics as a Markov process Describing Protein Folding Kinetics by Molecular Dynamics Simulations. Automatic discovery of metastable states for the construction of Markov models of macromolecular conformational dynamics
15	Calculation of protein-ligand binding Predicting Absolute Ligand Binding Free Energies to a Simple Model Site Principles of docking: An overview of search algorithms and a guide to scoring functions Alchemical Free Energy Calculations: Ready for Prime Time?	Hieu Nguyen
16	Protein Structure Determination New applications of simulated annealing in X-ray crystallography and solution NMR The molecular architecture of the nuclear pore complex

Systems Biology
17	Comparison of biological networks Modeling cellular machinery through biological network comparison Integrating physical and genetic maps: from genomes to interaction networks. Automatic Parameter Learning for Multiple Network Alignment
18	Building protein interaction networks High-quality binary protein interaction map of the yeast interactome network Empirically controlled mapping of the Caenorhabditis elegans protein-protein interactome network Literature-curated protein interaction datasets
19	Models and methods in systems biology Executable Cell Biology Computational Probability for Systems Biology Regulation of Gene Expression in Flux Balance Models of Metabolism	Daniel Kluesing
20	Learning networks from experimental data Causal Protein-Signaling Networks Derived from Multiparameter Single-Cell Data Predicting neuroendocrine tumor (carcinoid) neoplasia using gene expression profiling and supervised machine learning	Marc Schaub (part of lecture 19)

Population Genetics and Evolution
21	Identifying population structure and evolution Genes mirror geography within Europe Global distribution of genomic diversity underscores rich complex history of continental human populations Methods for Human Demographic Inference Using Haplotype Patterns From Genome-wide SNP Data	Marc Schaub (part of lecture 3)
22	Positive selection Patterns of Positive Selection in Six Mammalian Genomes Genome-wide detection and characterization of positive selection in human populations Signals of recent positive selection in a worldwide sample of human populations	Marc Schaub (part of lecture 3)
23	Human migrations A serial founder effect model for human settlement out of Africa The effect of ancient population bottlenecks on human phenotypic variation Worldwide Human Relationships Inferred from Genome-Wide Patterns of Variation	Jennifer Chen
24	Comparative genomics and evolution Forces Shaping the Fastest Evolving Regions in the Human Genome A Distal Enhancer and an Ultraconserved Exon are Derived From a Novel Retroposon Dispensability of mammalian DNA	Antony Vydrin
25	Stories of speciation Molecular and evolutionary history of melanism in North American gray wolves Genetic evidence for complex speciation of humans and chimpanzees
26	Ancestry inference Whole population, genome-wide mapping of hidden relatedness Effect of genetic divergence in identifying ancestral origin using HAPAA On the inference of ancestries in admixed populations
27	Haplotype reconstruction Bayesian Multi-Population Haplotype Inference via a Hierarchical Dirichlet Process Mixture Accounting for Decay of Linkage Disequilibrium in Haplotype Inference and Missing-Data Imputation	David Breeden

Bioinformatics and disease
28	Networks in disease The human disease network Protein networks in disease The implications of human metabolic network topology for disease comorbidity	Marc Schaub (part of lecture 19)
29	Methods in genome wide association studies Integrated genotype calling and association analysis of SNPs, common copy number polymorphisms and rare CNVs Practical Issues in Imputation-Based Association Mapping Resolving Individuals Contributing Trace Amounts of DNA to Highly Complex Mixtures Using High-Density SNP Genotyping Microarrays	Norú Moreno
30	From genome wide association studies to medicine Genetic Mapping in Human Disease Genetically Elevated C-Reactive Protein and Ischemic Vascular Disease Interpretation of Genetic Association Studies: Markers with Replicated Highly Significant Odds Ratios May Be Poor Classifiers	Florian Schmitzberger
31	Genomes and diseases DNA sequencing of a cytogenetically normal acute myeloid leukaemia genome Mapping and sequencing of structural variation from eight human genomes	Daniel Kluesing

Special topics
32	Imaging in biology Bioimage informatics: a new area of engineering biology Network Analysis of Intrinsic Functional Brain Connectivity in Alzheimer's Disease A Quantitative Spatiotemporal Atlas of Gene Expression in the Drosophila Blastoderm
33	Metabolic engineering Metabolic engineering of microorganisms for biofuels production: from bugs to synthetic biology to fuels A Novel Semi-biosynthetic Route for Artemisinin Production Using Engineered Substrate-Promiscuous P450BM3 Metabolic engineering of microorganisms: general strategies and drug production	Lekan Wang
34	Self-assembly of DNA An information-bearing seed for nucleating algorithmic self-assembly Combining Self-Healing and Proofreading in Self-Assembly Toward Reliable Algorithmic Self-Assembly of DNA Tiles: A Fixed-Width Cellular Automaton Pattern
35	Transforming cells into automata A universal RNAi-based logic evaluator that operates in mammalian cells Robustness analysis and tuning of synthetic gene networks

Schedule

As the quarter progresses, the following schedule will be updated accordingly. Please check back often for the latest material.

	Date	Title
		Presenter	Summaries	Critique
1	3/31	Introduction
		Serafim Batzoglou Marc Schaub		No critique
2	4/2	Human population genetics
		Serafim Batzoglou		No critique
3	4/7	Methods for high throughput population genetics
		Marc Schaub		No critique
4	4/9	Inference of phylogenetic trees
		Zinnia Zheng
5	4/14	Methods in genome wide association studies
		Norú Moreno		Jennifer Chen
6	4/16	Research presentation
		Marc Schaub		No critique
7	4/21	Human migrations
		Jennifer Chen	1 2 3	Hieu Nguyen
8	4/23	Nucleosome positioning
		Gus Katsiapis		Lekan Wang
9	4/28	From genome wide association studies to medicine
		Florian Schmitzberger	1 2 3 4	Norú Moreno
10	4/30	Haplotype reconstruction
		David Breeden	1 2 3
11	5/5	Metabolic engineering
		Lekan Wang	1 2	Zinnia Zheng
12	5/7	Models and methods in systems biology
		Daniel Kluesing	1 2	Antony Vydrin
13	5/12	Calculation of protein-ligand binding
		Hieu Nguyen	1 2
14	5/14	Comparative genomics and evolution
		Antony Vydrin		Florian Schmitzberger
15	5/19	No class (RECOMB'09)

16	5/21	No class (RECOMB'09)

17	5/26	Recomb recap
		Marc Schaub		No critique
18	5/28	Genomes and diseases
		Daniel Kluesing		Gus Katsiapis
19	6/2	Networks in diseases
		Marc Schaub	1	No critique
20	6/5	No class (Day before finals)

21		Summaries on other topics
			1 2
Sample entry from previous year:
		Microarray Analysis and Clustering
		Yu Bai	1 2 3