Transcript Miniature Liquid Fuel-Film Combustor Trinh Pham Derek Dunn

ChIP-Seq data analysis tool
Team Members: Natalia Shatokhina
Faculty Advisor: Dr. Russell Abbott, Dr. Sandra Sharp
Liaison: California Institute of Technology
Department of Computer Science
College of Engineering, Computer Science, and Technology
California State University, Los Angeles
Sponsor
Logo
Background
Development of computational approaches to interpret genomic data is a recent
research topic of many biology research groups. These methodologies allow
biologists to develop large-scale models of transcriptional and genetic regulation
to study certain biological processes. The myogenesis or muscle development
process is the one of the interest for Dr. Barbara Wold's Lab at Caltech and Dr.
Sandra Sharp at Cal State LA. The experiments using ultra-high throughput
sequencing methods are performed that can identify all the RNAs that are being
expressed in a muscle cell at given time (RNA-Sequencing method), and identify
all the locations in the genome at which a particular regulatory protein has bound
to the DNA (Chip-sequencing method). By processing all this information a model
of regulatory network is developed.
Objectives
To
help
to
analyze
the
experimental
data
a
computational biology tool was
developed that can be used in
processing of result sets from
experiments done with ChIP-Seq
methods. The goal is to provide
an interface to query for certain
kind of information. The type of
input data are the result sets
from ChIP-Seq experiments and
sets of genes. Typical result set
from
Chip0seq
experiment
contains a list of binding sites
(regions) for one particular
protein and some additional
information
relevant
to
experiment. Typical set of genes
is a list of genes containing their
id's, abbreviations and DNA
information
(coordinates,
chromosome). One set of genes
is named gene model.
User tools:
-to import result sets from file and store them in the database. The corresponding description of the result set is stored
in the -database as experiment description.
-to import gene models from file and store them in the database. The corresponding description of the gene model is
stored in the database as experiment description.
-to calculate overlaps between different sets of regions on a group of result sets or one result set
-to calculate distances from set of regions to gene model. Set of regions or result set from experiment and gene model
are specified by user (selected or uploaded from a file).