Starting from the comparison between fundamental stuff like geographical map, periodical table and the DNA code(genome map), Eric Lander focused on the information view of human genome.
Given a large topic, he could easily go from top to down(details) and then goes from bottom to top.
Important directions in genome project(he called todo list)
- understand all the functional elements of human genome(esp non-coding elements) by comparative genomic approach. eg, 4 close genomes for yeast, 25 mammalian genomes for human to understand non-coding elements. (he used a notion from Michael Waterman that human genome is 20 times larger than yeast's so that a log transformation means 4*log(20,a) ?= 25, but i didn't get the log transformation) These non-coding regions have more types of structural changes, like frameshifts. 1.2% human genome is coding region. But 5% is conserved. The 3.8% non-coding conserved regions are gonna be very related to regulation.
- understand all genetic variation. This is related to what's so-called HapMap project which is anounced (nearly)finished on Oct 6, 2005. We human have 1 per 1300bp variation, compared with chimp 1 per 800, gantun(wrongly spelled) 7 or 8 times more. So we have 2.5 million SNPs. These variations lead to the difference of susceptability to diseases, such as HIV. But we don't need to know all SNPs because they are dependent in a block way.
- understand the cell signature(gene expression). RNA space reflects the signature of each cell. Different cell types, different drug treatment, different genome content are all reflected by RNA space. The example is that under different drug treatment(2000 drugs), the cell exhibits different signature. The investigator compared the signature from different patients to them. Find the most similar and dissimilar and check the treated drugs. They found horrific discoveries.
- understand all significant changes related to cancer. The example is that different types of cancer show chunks of difference in different regions of genome(both sequence and gene expression).
- find inhibitors to all genes. RNAi consortium is almost finished halfway.
Whenever you look at the his own career(math, managerial economics, biology) or the things he talked, vision is very important.
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Joel Bader Seminar
Andrew Smith Seminar
Gene Regulatory Networks Special Feature (PNAS)
great vision
Given a large topic, he could easily go from top to down(details) and then goes from bottom to top.
Important directions in genome project(he called todo list)
- understand all the functional elements of human genome(esp non-coding elements) by comparative genomic approach. eg, 4 close genomes for yeast, 25 mammalian genomes for human to understand non-coding elements. (he used a notion from Michael Waterman that human genome is 20 times larger than yeast's so that a log transformation means 4*log(20,a) ?= 25, but i didn't get the log transformation) These non-coding regions have more types of structural changes, like frameshifts. 1.2% human genome is coding region. But 5% is conserved. The 3.8% non-coding conserved regions are gonna be very related to regulation.
- understand all genetic variation. This is related to what's so-called HapMap project which is anounced (nearly)finished on Oct 6, 2005. We human have 1 per 1300bp variation, compared with chimp 1 per 800, gantun(wrongly spelled) 7 or 8 times more. So we have 2.5 million SNPs. These variations lead to the difference of susceptability to diseases, such as HIV. But we don't need to know all SNPs because they are dependent in a block way.
- understand the cell signature(gene expression). RNA space reflects the signature of each cell. Different cell types, different drug treatment, different genome content are all reflected by RNA space. The example is that under different drug treatment(2000 drugs), the cell exhibits different signature. The investigator compared the signature from different patients to them. Find the most similar and dissimilar and check the treated drugs. They found horrific discoveries.
- understand all significant changes related to cancer. The example is that different types of cancer show chunks of difference in different regions of genome(both sequence and gene expression).
- find inhibitors to all genes. RNAi consortium is almost finished halfway.
Whenever you look at the his own career(math, managerial economics, biology) or the things he talked, vision is very important.