1 / 19

Genomics, Computing, Economics

Genomics, Computing, Economics. Tue & Thu 4:00-5:30pm HMS, TMEC L-007 . MIT-OCW Health Sciences & Technology 510 Harvard Biophysics 101  For more info see: http://openwetware.org/wiki/Harvard:Biophysics_101/2009. Genomics, Computing, & Economics Course plan.

arav
Download Presentation

Genomics, Computing, Economics

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Genomics, Computing, Economics Tue & Thu 4:00-5:30pm HMS, TMEC L-007  MIT-OCW Health Sciences & Technology 510 Harvard Biophysics 101  For more info see: http://openwetware.org/wiki/Harvard:Biophysics_101/2009

  2. Genomics, Computing, & Economics Course plan Each student will participate in a class-wide project to provide decision-making tools for global/local technology development and deployment. Each will have a web page or wiki describing and updating their part of project going by the second class. Grades will be based on 25% participation(round robin), 25% personal wiki page (weekly) 25% contribution to group project/ article, 25% peer evaluations No prerequisites. It is assumed that each of you brings some expertise to be integrated with the goals and talents of other team members. Each student should make this clear at the start of the project and update it as the course proceeds.

  3. Genomics, Computing, Economics & SocietyCourse plan This course will focus on understanding aspects of modern technology displaying exponential growth curves and the impact on global quality of life through a weekly updated class project integrating knowledge and providing practical tools for political and business decision-making concerning new aspects of bioengineering, personalized medicine, genetically modified organisms, and stem cells. Interplays of economic, ethical, ecological, and biophysical modeling will be explored through multi-disciplinary teams of students, and individual brief reports. Specific (standard) skills to be developed: statistics, modeling, datamining, systems biology, technology development.

  4. 101: '99-'03 Simple to Complex '05-’09 Complex to Simple • '03 5 problem sets then project • '09 Project starts on day 1 • '03 one 2 hr ppt lecture + 1.5 hr section per week • '09 two 1.5 hr discussion (may include 30' ppt) • '03 Project teams of 1 or two students • '09 Project team of all students & TFs • '03 Choice of two campuses & streaming video • '09 Less choice • '03 Tools: Perl & Mathematica • '09 Wiki (& anything else, especially Python)

  5. Previous class projects  Kim JI, .. Wu X, .. Seo JS (2009) A highly annotated whole genome sequence of a Korean Individual. Nature 460:1011-5.  Drmanac R, .. Wu X, .. Reid CA (2009) Human Genome Sequencing Using Unchained Base Reads on Self-assembling DNA Nanoarrays. Science submitted. André Catic, Cal Collins, George Church, Hidde Ploegh, HL (2004) Preferred in vivo ubiquitination sites. Bioinformatics 20: 3302-7. Andrew Tolonen, Dinu Albeanu, Julia Corbett, Heather Handley, Charlotte Henson & Pratap Malik (2002) Optimized in situ construction of oligomers on an array surface. Nucleic Acids Research, 30: e107 Hui Ge, George Church, Marc Vidal (2001) Correlation between transcriptome and interactome data obtained from S. cerevisiae. Nature Genetics, 29:482-6. John Aach, Martha Bulyk, George Church, Jason Comander, Adnan Derti, Jay Shendure(2001) Computational comparison of two draft sequences of the human genome. Nature 409, 856-859.

  6. Potential class projects 2009 H. sapiens 2.0 Analytic: Intra-species resources: Trait-o-matic: What could we do with 100,000 full genome sequences? Inter-species resources: comparative genome & phenome data Bioweather map: Collection & use of real-time assays to track outbreaks, etc. Synthetic: Cell therapies, environmental changes, etc. Resources: Biobricks, IGEM, HSCI SynBERC: Tumor Killing Bacteria

  7. Computational Approaches What is there? Informatics What is best? Optimization How do we get there? Simulation Hypothesis/opinion: DNA computers are poor at mathematics. Electronic computers are poor at predicting phenotype from DNA.

  8. The Maslow pyramid, 1943 Transcendence : need to help others find fulfillment Thirst for knowledge & aesthetical order Act Wisdom Knowledge Information Intelligence Memory Capacity

  9. 3 Exponential technologies(synergistic) Computation & Communication (bits/sec) E.coli operons Synthesis (daltons) tRNA urea B12 Analysis (bp/$) telegraph tRNA Shendure J, Mitra R, Varma C, Church GM, 2004 Nature Reviews of Genetics. Carlson 2003 ; Kurzweil 2002; Moore 1965

  10. Seq bp/$ 4 logs in 4 years $/genome 2009:Lig:$5K Pol:$50K (Moore’s law) 1.5x/yr for electronicsvs 10x/yr for DNA Sequencing 2005:capil:$50M 1995:gel: $3G 20 years ahead of the 1970-2004 exponential

  11. 1200kb/$ 30kb/$ Gene synthesis is still 1st generation Moore’s law (= 1.5x/yr)vs 10x/yr for 2nd-generationSequencing&DNA synthesis 2 b/$

  12. 101: '99-'03 Simple to Complex '09 Complex to Simple • Common ground; de-polarization. • What is life? Should we construct from scratch? • Did life evolve using intelligent design? • When does human life begin? • Stem cells & therapeutic cloning? • Can we compare Apples & oranges? • Should we buy iron-lungs • or polio-vaccine research? • Do we invest in anti-terrorism • or anti-malaria?

  13. It seemed like a good idea at the time. Crops River life Grain trade Livestock Hygiene Fertilizer Insecticides Pets Tankers Power Plants http://www.primitivism.com/easter-island.htm

  14. It seemed like a good idea at the time. Unintended consequences Crops River life Grain trade Livestock Hygiene Fertilizer Insecticides Pets Tankers Power Plants Malaria Cholera Yersinia Flu & HIV Polio Anoxic fish Silent Spring (> malaria) Australian herbicide Mussels & sea snakes Chernobyl (> coal) http://www.primitivism.com/easter-island.htm

  15. Precautionary Principle If an action might cause severe or irreversible harm to the public, in the absence of a scientific consensus, the burden of proof falls on those who would advocate taking the action. Downsides: • In a changing world inaction can be the radical “action” • Clean Air Act : incentive to use less well studied agents • Drugs & vaccines: more people can die than are saved • Thresholds & selective politically-motivated application Safety-by-Design • Inclusion of diverse community input (including out-of-the-box negative and safety scenarios) , simulation, controlled incremental tests, extensive cost-effective monitoring

  16. 1. Write your name, email, school & year. 2. Estimate 8 x 7 x 6 x 5 x 4 x 3 x 2 x 1 3. From a group "of 70 engineers and 30 lawyers: Dick is a 30 year old man. He is married with no children. A man of high motivation, he promises to be quite successful in his field. He is well liked by his colleagues." What is the probability that Dick is an engineer? Human subject experimentation(not a test) 7 questions. 5 seconds each 4. Write down a string of 10 random H & T characters. 5. From 10 people, how many different committees of 2 members? and of 8 members? 6. One individual has drawn 4 red balls and 1 white. Another 12 red and 8 white. What odds should each individual give that the source is 2/3 red (rather than 2/3 white)? 7. Estimate 1 x 2 x 3 x 4 x 5 x 6 x 7 x 8

  17. "Economics has been regarded as a non-experimental science, where researchers – as in astronomy or meteorology – have had to rely exclusively on field data, .. however, these views have undergone a transformation. Controlled laboratory experiments have emerged as a vital component .. & have shown that basic postulates in economic theory should be modified. .. cognitive psychologists who have studied human judgment and decision-making, and experimental economists who have tested economic models in the laboratory. .. Daniel Kahneman and Vernon Smith." (see also: Judgement under Uncertainty 1974 Science 185:1124) Cognitive bias .. includes "very basic statistical and memory errors that are common to all human beings and drastically skew the reliability of anecdotal and legal evidence & significantly affect the scientific method." Economics Nobel 2002

  18. #!/usr/bin/env python from Bio import GenBank, Seqquery = "Arabidopsis[ORGN] AND topoisomerase[TITL]"print "Query:", query # GenBank.search_for() returns a list of genbank ids in response to the querygi_list = GenBank.search_for(query)print "GenBank ids returned:", gi_list# NCBIDictionary is an interface to Genbank# If you pass it an id, it will download the raw recordncbi_dict = GenBank.NCBIDictionary('nucleotide', 'genbank')# Retrieve the first 2 resultsraw_records = []for i in range(2): raw_records.append(ncbi_dict[gi_list[i]])# Here we print the raw record from the first id returned by our queryprint "\nrecord 1:\n", raw_records[0]# We can also create an interface that will parse the raw record# This facilitates extracting specific information from the sequencesrecord_parser = GenBank.FeatureParser()ncbi_dict2 = GenBank.NCBIDictionary('nucleotide', 'genbank', parser = record_parser)parsed_record = ncbi_dict2[gi_list[0]]print "\nid:", parsed_record.idprint "sequence:", parsed_record.seq.tostring() Programming

  19. Read the HELP page to get acclimated to the wiki environment if you are not already familiar with it. You will be documenting the majority of your class contributions on this wiki. Sign up for an OpenWetWare account HERE and add yourself to the PEOPLE page. Write a brief description about yourself, your interests and what you hope to get out of the class in your own user page. Sept 3, 2009 Assignment

More Related