The recent completion of the human genome project underlines the need for new computational and
theoretical tools in modern biology. The tools are essential for analyzing, understanding and manipulating the detailed information
on life we now have at our disposal. Problems in computational molecular biology vary from understanding sequence data to the analysis of protein shapes,
prediction of biological function, study of gene networks, and cell-wide computations. Cornell has a university-wide plan in the science of genomics; the Department of Computer Science is playing a
critical role in this initiative. Researchers in the computer science department are engaged in a wide range of
computational biology projects, from genetic mapping, to advanced sequence analysis, fold prediction, structure
comparison algorithms, protein classification, comparative genomics, and long-time simulation of protein molecules. Faculty and Researchers Adam Siepel has worked on various problems in
computational biology, including the detection of recombinant viruses, the reconstruction of evolutionary histories based on
genome rearrangements, and the integration of heterogeneous bioinformatics software tools. His most recent work has been in
comparative genomics, particularly of mammals, and has included a mixture of statistical modeling, algorithms development,
software implementation, and scientific discovery. Adam likes to tackle problems of practical importance in genomics,
such as gene finding and conserved element identification, using methods from machine learning and statistics. He is an
active participant in several large-scale comparative genomics projects, including the Mammalian Gene Collection project,
the ENCODE project, and the Rhesus Macaque Sequencing and Analysis Consortium. Carla Gomes works on solutions to hard combinatorial problems, with
an emphasis on planning and scheduling problems, combining techniques fromm Computer Science (CS), Artificial Intelligence (AI), and
Operations Reserach (OR). Her research is leading to the creation of the new field of computational sustainability,
which develops and applies computational methods to enable a sustainable environment, economy and society. Klara Kedem 's research area is Computational Geometry. Her
current research interest include applications of pattern matching and shape matching to ares bioinformatics, computer vision,
and historical document analysis. With colleagues she discovered the minimum Hausdorff distance for image comparison, and
developed a new metric, the URMS, to compare protein shapes. Recent extensions to this method, based on geometric dynamic
programming, were applied to compute consensus shapes for protein families. At Ben-Gurion University Klara studied dendrite
shapes with colleagues from the Life Sciences Dept. and collaborates with the Chemistry Dept. on finding similarities between
conformational polymorphs. Recently she has been working on searching structural RNA motifs in large databases. Uri Keich is working on statistical and algorithmic
problems that arise in amino acid and DNA sequences analysis. He worked on finding motifs or highly preserved sub-sequences
which are presumably of biological importance. This problem poses an algorithmic challenge as well as a statistical one:
classical statistical approximations break down when applied to analyzing the statistical significance of a detected motif.
While Uri worked on both aspects of the problem his current research focus is mostly on designing computational statistical
tools that would be robust enough to correctly handle the extreme values one typically encounters in this context. Some of these
techniques are brought to bear in a recently established collaboration with biologist Bik Tye studying replication initiation in
strains of yeast. Jon Kleinberg 's research focuses on algorithmic
issues at the interface of networks and information. In the area of computational biology, he has worked on algorithms for the
construction of comparative genomic maps (jointly with Prof. Susan McCouch from Plant Breeding and Ph.D. student Debra Goldberg).
He is also studying sequence-structure relationships in proteins and the `connectivity' of protein families via mutations in
sequence space (joint work with Prof. Ron Elber). David Shmoys is studying approximate algorithms
for genetic linkage mapping (identifying the locations of markers on the genome) to reduce the cost of wet lab experiments and
improve the accuracy of the resulting maps. Education
A new graduate program in
Computational Molecular Biology that crosses colleges was initiated
with the participation of the computer science field. | Researchers Adam Siepel
Carla Gomes
Klara Kedem
Uri Keich
Jon Kleinberg
David Shmoys
Programs Graduate program in Computational Biology
Tri-institutional Program in Computational Biology and Medicine Related Links Institute for Computational Sustainability |
