Transcript Internship Sites - California State University, Los Angeles

Internship Site #1
• BioDiscovery
• Lead mentor: Bruce Hoff, Ph.D.
• Students will use BioDiscovery’s software tools to
analyze gene or protein microarray data that is
provided by another participating site. Students will
provide critical feedback regarding the applicability of
the software to a given analysis and will share ideas
for novel tools. The BioDiscovery software will be
either current format or prototype extensions, and the
student may be involved in development of new tools.
Internship Site #2
• Chen Laboratory, University of Southern California (be
sure to use the link to Dr. Chen’s research homepage)
• Lead Mentor: Tim Ting Chen
• Dr. Chen works on genome assembly, gene-finding,
genome rearrangements, mass spectrometry data
analysis, microarray data analysis and protein-protein
interactions. Possible projects: development of
programs and user-interface for mass spectrometry
data analysis; development of methods and tools for
analyzing protein-protein interaction networks; and the
development of tools for microarray data analysis.
Internship Site #3
• Larson Laboratory, Division of Molecular Medicine,
Beckman Research Institute, City of Hope
• Lead mentor: Garry Larson, Ph.D.
• Dr. Larson, together with Dr. Ted Krontiris, seeks to
identify disease alleles and gene interactions in
candidate genes important in risk assessment for
cancer (predominately breast and prostate).
Research involves microsatellite, microarray
expression, associated transcription factor binding
site, and SNP analyses on DNA from cancer patients
who are sibling pairs.
Internship Site #4
• Nordborg Laboratory, University of Southern California
• Lead Mentor: Magnus Nordborg, Ph.D.
• Dr. Nordborg focuses on natural variation in the model
organism, the plant Arabidopsis. He is constructing a
haplotype map for this species. Possible projects:
construction of web-interfaces for visualizing data,
database programming, implementation of analysis
methods, automation of post-processing of sequence
data.
Internship Site #5
• Protein Pathways
• Lead Mentor: Matteo Pellegrini, Ph.D.
• Development of computational techniques to
reconstruct protein networks from genome sequences,
expression microarray and literature data. Possible
projects: extension of network methodologies,
development of dynamic network models that account
for molecular concentrations and their fluctuations,
methodologies to discover the states of proteins and
their biological impact, and novel methods to
determine drug-protein associations.
Internship Site #6
• Vialogy
• Lead mentor: David J. Robbins, Ph.D.
• Dr. Robbins is a specialist in the area of active signal
processing and quantum resonance interferometry (QRI). He
has been working on developing applications of active signal
processing to biomedical instrumentation. Applications have
included analysis of DNA microarray data and DNA sequencing
data. Possible projects: development of more sensitive
analyses of microarray data, real-time PCR, 2-D gels, and
mass spectrometry data. Students will learn how to evaluate
analytical technologies currently used in the pharmaceutical
and biotech fields. They will participate in the design of studies
that must address the issues of concern for both the
manufacturers and the users, and will determine the added
value needed to justify incorporation of QRI into the current
analytical technologies.
Internship Site #7
• Wold Laboratory, Caltech
• Lead Mentor: Barbara Wold, Ph.D.
• Dr. Wold is interested in cell differentiation pathways
and cell simulation. She investigates pathways by
means of microarray analysis. Her group has used
both synthetic and biological microarray data to
undertake critical analyses of the efficacy of clustering
algorithms for inferring transcriptional regulatory
pathways. Possible project: population of a pathway
database with literature-supported reactions and rate
constants suitable for computational modeling of
pathways.
Internship Site #8
• Yeates Laboratory, UCLA
• Lead Mentor: Todd Yeates, Ph.D.
• Yeates’ group has developed a set of computational
approaches for assigning functions to novel protein sequences
and for elucidating the way proteins are connected into
functional networks in the cell. In more recent work his group
has made a surprising bioinformatics discovery -- in a certain
branch of the phylogenetic tree, archaeal microorganisms have
intracellular proteins that are rich in disulfide bonds. The group
is currently investigating both the scientific implications and the
potential practical applications arising from this discovery, and
will be using new proteomics methods in their approaches.
Possible projects: bioinformatics approaches to functional
genomics and proteomics of archeabacteria; use of novel
modeling software to compare classes of proteins from bacteria
and other microorganisms.
Ranking of Internship Preferences
• In order to make internship assignments that will be mutually
rewarding, we will be taking into account
– your level of interest in each group
– comments from prospective mentors
– your academic, research, and professional experience
• for six sites, we will be attempting to assign teams of two
with combined expertise in biological and computerrelated sciences
• Please fill out the attached Word document (Internship
Preferences.doc) and email it as an attachment to
[email protected] no later than 9 AM, Wednesday, June
18th. If you are unable to email, turn it in as hardcopy in the
morning session, June 18th.
• We will do our best to match you with one of your first three
choices.