Announcements
See our lecture series
Our 2nd Kick-Off event to introduce the interdisciplinary program in Quantitative Biology to the Hunter College Community
Come meet with program coordinators from the four departments, learn about the program and get your questions answered
Tuesday, November 24, 2009
7pm - 8pm
HN 926
First Hunter student to obtain QuBi scholarship
The first QuBi scholarship granted to a student in the bioinformatics program has been awarded by the Dean of Students in Fall 2009 to Ilya Korsunsky, a Computer Science major pursuing the bioinformatics concentration.
2009 Summer Workshop in Quantitative Biology/Bioinformatics
This workshop, given for the first time, was an introductory course, with no pre-requisites, designed to make it easier for students to enter the new fields of bioinformatics and computational genomics. It was taught in a new LINUX-based computer lab, offering hands-on experience in bioinformatics.
The QuBi External Advisory Committee visited Hunter on June 22nd and 23rd, 2009
Its members are:
Prof. Matthew Johnson, Chair of the External Advisory Committee
Statistics & Education
Columbia University, Teachers College
Prof. Stephen Aley
Biological Sciences
University of Texas, El Paso
Prof. Joseph Chang
Statistics Department
Yale University
Prof. Jacques Cohen
Computer Science
Brandeis University
Prof. Bert Flugman
Center for Advanced Study in Education
The Graduate Center of CUNY
Lecture Series
Computational Modeling for Biological Systems
Speaker: Nancy Griffeth, Department of Mathematics and Computer Science, Lehman College of CUNY
Date: Friday, October 9, 2009
Time: 12:00 noon - 1pm
Room: HE 920
Intended for: Students and Faculty
Model checking has been a powerful tool for ensuring that computer hardware and software work correctly. Model checking provides for checking that all executions of the hardware or software of a system satisfy important properties - for example properties guaranteeing that the doses of radiation never exceed safe limits when using radiation therapy, or properties guaranteeing that automobiles never approach one another too closely. However, the success of model checking has been limited to discrete systems so far. In this talk I will describe a major new project to use model checking for hybrid systems, that is, systems including both discrete and continuous behaviors. The goal of the project is to address problems in biological systems - such as the growth of cancer cells - and in embedded systems - such as those controlling airplanes and automobiles.
Analysis of Hidden Markov Models Applied to Gene Finding
Speaker: Igor Balsim
Kingsborough Community College, Mathematics & Computer Science
Date: Friday, May 15, 2009
Time: 12:00 noon - 1:00 pm
Room: HN 310
Intended for: Students and Faculty
A
Hidden Markov Model (HMM) is a stochastic model that captures the
statistical properties of computational biology: protein family
profiling, protein binding site recognition, and gene finding in DNA, a
foremost computational biology problem to explain the molecular
interactions that occur in cells and to define important cellular
pathways. Applications of Hidden Markov Models (HMM) will be described
in general and specifically to classifying DNA bases according to which
type of job they perform during transcription. Given a sequence of DNA
identify for each nucleotides as belonging to coding regions in a gene,
non-coding regions in a gene, or intergenic regions. Annotate the sets
of genomic data with the specific areas such as promoter regions,
introns, and exons. A description will be presented how HMM is used to
find protein coding genes in E.coli DNA using E.coll genome DNA
sequence from the EcoSeq6 database maintained by Kenn Rudd. This HMM
Includes states that model the codons and their frequencies In E.coli
genes, as well as the patterns found In the intergenic region. In
addition I will present statistical method to annotate alternatively
spliced exons using a single genome sequence, which us an important
challenge in eukaryotic gene prediction.
Scientific and Statistical Computing in the Cloud; towards a Federative and Collaborative R-based Platform
Speaker: Karim Chine
European Bioinformatics Institute, Imperial College of London, UK
Date: Wednesday, April 1, 2009
Time: 2:30 pm- 3:30 pm
Room: HE 920
Intended for: Students and Faculty
We proposed to build on top of R an open platform for computing and
data analysis. Using a rich workbench within the browser, the
statistician can now work with an R server running at any location as
if it is on his local machine. The platform hides the complexitiy of
High Performance Computing or Cloud Computing infrastructures, and
enables collaborative data analysis of large data sets. This lecture
will give an overview of the new platform. Biocep's deployment on
Amazon EC2 wll be demonstrated.
Oncology Biomarkers and Personalized Medicine
Speaker: Hyerim Lee, Merck & Co.
Date: Friday, March 27, 2009
Time: 3:00 pm- 4:15 pm
Room: HN 310
Intended for: Students and Faculty
Personalized medicine refers to medical care tailored to individuals based on their genetic makeup, gene expression, proteins and/or metabolites. The development of personalized medicine becomes particularly important in cancer therapy, where only 20-30% of patients respond to drub treatment. This sobering fact calls for the development of genetic markers (biomarkers) to predict sensitivity and resistance to chemotherapeutic agents. This presentation focuses on the biomarker discovery effort for epothilone, a microtubule-stabilizing agent, and outlines how oncology biomarkers are identified and developed through preclinical and clinical studies.