GENE YEO

 

Curriculum Vitae (in pdf) (in html)

 

 

Salk Institute-CNL 10010 North Torrey Pines Road

La Jolla, CA 92037

Work Phone:
(858) 453 4100 ext 1067 (dry-lab) or ext 1009 (wet-lab)

geneyeo at salk.edu

 

 

 

 

 

You shall no longer take things at second or third hand, nor look through the eyes of the dead, nor feed on the spectres in books,

 

You shall not look through my eyes either, nor take things from me,

 

You shall listen to all sides and filter them from your self...Walt Whitman

What's in the works

 

October 1st 2008. I've recently started my new job as an assistant professor at UCSD's department of cellular and molecular medicine, and am faculty in the UCSD Stem Cell Program, Biomedical Sciences and Bioinformatics Graduate Programs .

2nd May 2008. A collaboration on analyses of piRNAs in planarian regeneration with Brenton Graveley has been published at RNA .

9th November 2007. A collaboration on analyses of small RNAs from Dicer knockout mouse ES cells with Mauro Calabrese and Amy Seila at Phillip Sharp's lab at MIT has recently been published at PNAS .

19th October 2007. I gave a talk at the 2nd Annual Stem Cell on the Mesa conference, which was a really fun one day conference held at the Salk. The program is listed here .

October 2007. I'm very honored to play a small part in a paper with Brent Graveley, Marco Blanchette, Joanne Yeakley, Yiannis Savva and Don Rio identifying a Regulator of Dscam Mutually Exclusive Splicing Fidelity .

September 2007. We recently published a method we call REAP (Regression-based Exon Array Protocol) for Affymetrix Exon Array analysis and applied it to identifying alternative splicing changes during neural progenitor specification during human embryonic stem cell differentiation. We are currently performing RNAi knockdowns of particular splicing factors in ES cells. I've deposited the CEL files here

August 2007. Together with Melissa Moore at Brandeis (now at U Mass Medical), we published a recent study showing that a splicing associated factor can modulate synaptic strength and neuronal expression, and we've identified ~100 other candidates genes with conserved introns in the 3'UTR.

June 2007. We published a set of intronic splicing regulatory elements identified in the mammalian genomes. We are currently performing experiments to identify their RNA binding partners. I've deposited the Intronic Splicing Regulatory Elements here

I'm a Junior Fellow at the Crick-Jacobs Center for Computational and Theoretical Biology at the Salk Institute and my fellowship mentors are Rusty Gage and Sean Eddy. Among other goals, one of my objectives here is to uncover the impact of alternative splicing on adult neuronal stem cell differentiation. I'm also involved with exciting collaborations with other groups in the United States and in Singapore. In particular, I am interested in pursuing more cross-continental joint projects to train the next generation of young researchers in Singapore.

I completed my Ph.D. in Computational Neuroscience at MIT under the supervision of Prof. Christopher Burge (Dept. of Biology) and Prof. Tomaso Poggio (Computer Science and Artificial Intelligence Laboratory, McGovern Institute for Brain Research, Dept. of Brain and Cognitive Sciences, Center for Biological and Computational Learning). I continued as a postdoc from Dec 2004 to March 2005, before starting at the Salk Institute.

 

See article about alternative splicing in the Sept 05 HHMI bulletin. Download pdf from the HHMI website .

 

 

 

RESEARCH INTERESTS

 

My primary research interest is to understand the molecular network-level changes during the specification of neural/neuronal stem cell fate from human/mouse ES and neural stem cells. Specifically, I am interested in (1) identifying alternative splicing (AS) events that are crucial for fate specification, and the RNA binding proteins (splicing factors) that regulate these AS events; and (2) analyzing the small RNA repertoire that change during fate specification. My secondary research interest is in molecular sequence evolution using multiple genomes, which I use as a basis for the systematic computational discovery of RNA regulatory elements important in post-transcriptional processing, such as elements important for alternative splicing and RNA stability. I pursue my objectives with multidisciplinary techniques ranging from developing my own computational tools (machine learning, statistical sequence analysis, graphical modeling), using molecular and cell biological approaches, and coupled with high-throughput approaches (high-density Exon Arrays, 454 or Solexa deep sequencing).

 

PHD DISSERTATION Download pdf

My thesis work focused on developing a hybrid of computational and experimental methods to identify and model cis-regulatory sequence elements that regulate both constitutive and alternative splicing in eukaryotic genomes, integrating these models to predict constitutive and alternative exons conserved in mammalian genomes in silico, followed by in vivo experimental validation.

 

QUICK LINKS

 

PubMed
Google

Summer triathlons
convexity
WI Library

Linear Methods in Matlab
Statistics lecture notes
Walt Whitman Archive

C programming

Pointers and Arrays in C
One Liners Shell Programming

MathSciNet

Web of Science
Taxes
US Patent Office
Webster's Dictionary

 

COMPUTATIONAL BIOLOGY/ BIOINFORMATICS

 

UCSC Genome Browser

Ensembl Genome Browser

Perldoc for BioPerl; Bioperl Open Source

BioBase (Transfac etc)

DNA/RNA sequence analysis Tools

PFAM; RFAM; RIO

Codon Table in Java

SNP Consortium (CSHL)

Virtual Library of Biochemistry and Cell Biology

 


SELECTED PUBLICATIONS

 

Bold represents first authorship. Underline represents papers where I am co/corresponding author.

 

The PIWI proteins SMEDWI-2 and SMEDWI-3 are required for stem cell function and piRNA expression in planarians.

Palakodeti D., Smielewska M., Lu Y, Yeo, G.W. , Graveley B.R. RNA 2008

 

RNA sequence analysis defines Dicer's role in mouse embryonic stem cells.

Calabrese J.M., Seila, A.C., Yeo, G.W., Sharp, P.A. PNAS 2007

 

Alternative Splicing Events Identified in Human Embryonic Stem Cells and Neural Progenitors

Yeo, G., Xu, X, Liang, T.Y., Muotri, A.R., Carson, C.T., Coufal, N.G., Gage, F.H. PLoS Computational Biology 2007

 

The EJC factor eIFAIII modulates synaptic strength and neuronal protein expression

Giorgi. C, Yeo, G., Stone, M.E., Katz, D.B., Burge. C., Turrigiano, C., Moore, M.J. Cell 2007

 

Discovery and analysis of evolutionarily conserved intronic splicing regulatory elements in mammalian genomes.

Yeo, G, Van Nostrand, E, Liang, Y.T. PLoS Genetics 2007 ISRE datasets

 

Inference of splicing regulatory activities by sequence neighborhood analysis.

Stadler M.B., Shomron N, Yeo G.W., Schneider, A, Xiao, X, Burge C.B. PLoS Genetics 2006

 

Noncoding RNAs in the Mammalian Central Nervous System

Xinwei Cao, Gene Yeo, Alysson Muotri, Tomoko Kuwabara, Fred H. Gage Annual Review of Neuroscience 2006

 

Minireview: Splicing regulators: targets and drugs

Yeo, G Genome Biology 2005

 

A Combinatorial Code for Splicing Silencing: UAGG and GGGG Motifs.

Han, K.H., Yeo, G, An, P., Burge, C.B. and Grabowski, P. PLOS Biology 2005

 

Identification and analysis of alternative splicing events conserved in human and mouse.

Yeo, G, Van Nostrand, E, Holste, D, Poggio, T and Burge, C.B. PNAS 2005.

 

Systematic identification and analysis of exonic splicing silencers.

Wang, Z, Rolish, M, Yeo, G, Burge C.B. Cell, 2004.

 

Variation in alternative splicing across human tissues.

Yeo, G, Holste D, Kreiman, G, and Burge, C.B. Genome Biology, 2004.

 

Variation in the splicing regulatory elements and their organization in vertebrate genomes.

Yeo, G, Hoon S, Venkatesh, B, and Burge, C.B. PNAS, 2004.

Fish genes work in human cells.; Making fish genes work in human cells.

 

Maximum entropy modeling of short sequence motifs with applications to RNA splicing signals

Yeo, G, and Burge, C., RECOMB03 and Journal of Computational Biology, 2004.

 

Regularized Least-squares Classification.

Rifkin, R, Yeo, G and Poggio, T.  Advances in Learning Theory: Methods, Model and Applications, NATO Science Series III:  Computer and System Sciences, Vol. 190, ISO Press, Amsterdam 2003.  Edited by Suykens, Horvath, Basu, Micchelli and Vandewalle.

 

 
THE COMPLEXITY OF RNA
 The RNA World Website

Structural Classification of RNA

 

CONSTITUTIVE & ALTERNATIVE SPLICING

GENE's ALGORITHMS:

Maximum Entropy Splice Site Model (MaxENTScan)

RESCUE-ESE Webserver

ACEScan Webserver

 
JOURNALS
Human Molecular Genetics
Bioinformatics
EMBO Journal Online
J. Biological Chemistry
Science
Nature
Nature Neuroscience
Nature Biotechnology
Cell Online
Immunity
Modern Drug Discovery
PNAS
The Lancet
New England Journal Of Medicine
Signals
New Scientist
American Scientist
HMS Beagle
Chemical & Engg News
The Daily Apple
AICHE Online Community

 

 
COLLABORATORS

Phillip Sharp
Melissa Moore
Brenton Graveley
Xiang-dong Fu
Amy Pasquinelli
Anastasia Zimmerman

 
NEWS

ASTAR
Bio*One Capital
New York Times
Wall Street Journal
CNN
The Economist
Straits Times
SF Gate

 

 
INFORMATION THEORY/ MACHINE LEARNING

Introduction to Information Theory/ Entropy

Jayne's Book

Adam Berger's Links (Maximum Entropy)
Research Index
SVM Light  
 

 
PEOPLE LINKS

Sean Eddy

Terry Sejnowski

Fred Gage

David Bostein, Lewis-sigler

David Haussler

Manny Ares

Mike Eisen

Pat Brown

Ron Davis

David Bostein

Michael Snyder

Thomas Gingeras

Phillip Sharp

Robert Darnell

Thomas Cooper

Richard Gatti

Paula Grabowski

Xiang-dong Fu

 

 

 

CONSULTING

 

GeneBytes

Neuron Systems

 
BOSTON BIOTECH COMPANIES/ VENTURE

 

5AM ventures
Genomics Collaborative Inc
Variagenics
Vertex Pharmaceuticals
Novirio Pharmaceuticals
ViaCell
Biogen
Genzyme
Boston Scientific
MPM Capital
Millennium Pharmaceuticals