Simon Kasif's home page

Research Interests:

Computational Genomics, Bioinformatics, Probabilistic Modeling of Biological Systems, Computational Learning, Artificial Intelligence, Algorithm Design.

I have moved to Boston University

I shortened my commute to the nearest Genome Center to 7 minutes

Computational Genomics Laboratory

Graphical Models, Bayes Networks and Biology

Research Scientists and Postdoctoral Fellows

We are delighted to announce several research and visiting positions in Computational Biology and Bioinformatics at Boston University.
Boston University has an established tradition in computational approaches to biology, and BU programs in this area include several researchers such as Charles DeLisi who recentlly received the Presidential Medal of Honor for initiating the Human Genome Project , Robert Berwick, Charles Cantor, Jim Collins, Simon Kasif, Temple Smith, Sandor Vajda, Zhiping Weng as well as several associated faculty such as Rich Roberts, Chris Sander and Ken Fasman. We have active collaborations with The Institute for Genomic Research , MIT Genome Center, Berkeley Molecular Sciences Institute and local industry.
Boston University has established one of the first Ph.D. programs in Bioinformatics (see The program now enters its third year and has several research centers in related areas where students and faculty conduct research on a variety of topics in genomics, proteomics, gene regulation, genetic switches, computational biology and bioinformatics.
A new DNA chip manufacturing facility is built in collaboration with several groups on campus. A number of biotechnology start-up companies were recently spinned-off based on innovative ideas developed at Boston University.
We are seeking to fill several postdoctoral research positions at various levels (research scientist, senior postdoctoral fellow, postdoctoral fellow). The researchers will conduct directed and independent research in computational genomics, bioinformatics, computational biology, functional genomics and comparative genomics. Salaries will be determined based on qualifications.
High-quality applicants with background in computation and biology are particularly encouraged to apply. We will consider unusually strong applications from researchers seeking to enter bioinformatics from other fields such as physics, computer science, learning, mathematics or life sciences.
We also welcome applications for graduate study in bioinformatics, computational biology and computational genomics.
For information see, or send email to

Recent Publications in Computational Biology

Recent Resources:

Multiplex PCR Server: Genotyping, PCR Assays, Genome Walks, ,  "Rachlin, Ding, Cantor, Kasif

Recent Publications in Computational Biology Kasif publications


Selected Bioinformatics Publications  


Salzberg,S., D. Searl and S. Kasif,  "Computational Methods in Molecular Biology",Elsevier Publ., 1998.

International Human Genome Consortium,  "  Lander et al, Initial Sequencing and Analysis of the Human Genome",  Nature, February 2001

Delcher, A., S. Kasif, H. Goldberg and W. Xsu,  "Protein Secondary-Structure Modeling with Probabilistic Networks", International Conference on Intelligent Systems and Molecular Biology, pp. 109--117, 1993 . One of the first applications of Hidden Markov models and first application of probabilistic networks (Bayes Nets) to modeling proteins.

Salzberg, S., A. Delcher, S. Kasif and O. White,  "Microbial Gene Identification Using Interpolated Markov Models",  Nucleic Acids, 1997,  a widely used system for gene finding in microbial DNA.

Delcher, A.,  S. Kasif,  R. Fleischmann,  O. White and  S. Salzberg, "Whole Genome Alignment",  Nucleic Acids Research, pp. 2369--2376, 1999,  used in the Minimal Organism study at TIGR (Science 10/1999), used to detect chromosomal duplications in Arabodopsis (Nature 12/2000), used to detect inversions and large scale duplications in microbial genomes.

Delcher, A., D. Harmon,  S. Kasif,  O. White and S. Salzberg,  "Improved Microbial Gene Identification with Glimmer",  Nucleic Acids, Vol. 27, No. 23, pp. 4636--4641, 1999.  Glimmer II.

Tettelin, H. D. Radune, S. Kasif, H. Khouri, and S. Salzberg,  "Pipette Optimal Multiplexed PCR: Efficiently Closing Whole Genome Shotgun Sequencing Project", Genomics, Vol. 62, pp. 500--507, 1999.

Kasif,S., S. Salzberg, D. Waltz, J. Rachlin and D. Aha,  "Towards a ProbabilisticFramework for Memory-Based Reasoning",  Artificial Intelligence, November 1998.A early proposal for for combining generative models and supevised learning (classification).

S. Kasif,  "Datascope: Mining Biological Sequences", IEEE Intelligent Systems,  pp. 38--46,  1999.

Cai, D., B. Kao, S. Kasif and A. Delcher,  "Modeling Splice Sites Using Bayes Networks'', Bioinformatics, 2000.

Pavlovic, V., A. Garg and S. Kasif, "A Bayesian Framework for Combining Gene Predictions",  Computational Genomics Nov. 2000.

A. Delcher, A. Grove, S. Kasif and J. Pearl, Logarithmic Time Query-Update Inference Algorithms in Bayesian Networks", Journal of Artificial Intelligence, 1996. An early theoretical proposal for deploying Bayesian Networks for Perturbational Analysis in Biological Systems

Beigel, R., N. Alon, S.M. Apaydin, L. Fortnow and S. Kasif,  "An Optimal Multiplex PCR Protocol for Closing Gaps in Whole Genomes",  Computational Genomics, Nov 2000.

B. Logan, P. Moreno, B. Suzek, Z. Weng and Simon Kasif,   "Remote-Homology Detection Using Feature Vectors", in review.

B. Suzek, S. Kasif, B. Logan and P. Moreno,  "Remote-Homology Detection Using Feature Vectors", in review.

Beigel, R., N. Alon, S.M. Apaydin, L. Fortnow and S.Kasif,  "An Optimal Multiplex PCR Protocol for Closing Gaps in Whole Genomes",  RECOMB 2001, ,  a theoretical treatment of multiplex PCR for GAP closing in whole genome assembly.

S. Kasif, "Efficient Gene Discovery by Database Matching",  by request.

Kasif, S., S. Banerjee, A. Delcher and G. Sullivan,  "Some Results on the Complexity of Symmetric Connectionist Networks",  Annals of Mathematics and Artificial Intelligence,  327-344,  Nov. 1993. 

Murthy, S., S. Kasif and S. Salzberg, "A System for Induction of Oblique Decision Trees'', Journal of Artificial Intelligence Research, 2:1 (1994),1--33,   a popular decision tree system.

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1*. Walker, M., V. Pavlovic, and S. Kasif "A Comparative genomic method for the identification of prokaryotic translation sites", Nucleic Acid Research, 2002.

An application of comparative product HMMs (a new methodology for comparative genomics) for bacterial start-site identification. This is an increasingly important problem because of the opportunity to use comparative analysis of up-stream sequences for binding site identification leading to understand regulation in bacteria.

2*. Zheng, Y., R. Roberts and S. Kasif, "Computational identification of operons in microbial genomes", Genome Research, 2002

Identification of complex operons in bacterial genomes. Applications include identification of polyketides for production of antibiotics.

3*. Zheng, Y., R. Roberts and S. Kasif, "Genomic functional annotation using co-evolution profiles of gene clusters, Genome Biology 2002.

Continued collaboration with Dr. Richard Roberts.

4*. Simon Kasif+, Zhiping Weng+, Richard Beigel, Charles DeLisi, "A Computational Framework for Optimal Masking in the Synthesis of Oligonucleotide Microarrays", Nucleic Acid Research 2002 (+ - contributed equally).

10-20% improvement in number of rounds needed to synthesize a microarray.

5*. Noga Alon, Richard Beigel and Simon Kasif and Steven Rudich and Benny Sudakov, "Learning a Hidden Matching", Proc. of Foundations of Computer Science (FOCS 2002), a theoretical treatment of multiplex PCR to close gaps in shot gun sequencing of genomes, joint project with Princeton Institute for Advanced Studies. Previous version of this algorithm has been used at MIT Genome Center and The Institute for Genomic Research to close the gaps in several major pathogens and archea.

6. Joseph D. Szustakowski, Ulas Karaoz, Serafim Batzouglou, James Galagan, Tarjei Mikkelsen, Zhiping Weng, Joel H. Graber, S. Kasif, On the Organization of Ancient and Modern Genes in the Human Genome, in review. (joint project with MIT Genome Center).

7. B. Logan, P. Moreno, B, Suzek and S. Kasif, "Learning Remote-Homology Using Probabilistic Feature Vectors", in review.

A new approach for classification of proteins into structural families.

8*. Yang Su, T. M. Murali S. Kasif, "RankGene", to appear Bioinformatics.

A system to identify diagnostic genes in microarray data.

9*. T. M. Murali and S. Kasif, "Discovering Conserved Gene Expression Motifs in Microarray Data", PSB 2002.

Identifying groups of genes whose expression profile is relatively conserved across a collection of conditions.

10*. J. Zhang, V. Pavlovic, C. Cantor, S. Kasif, "Cross Species Gene Identification in Human and Mouse Sequences using Evidence Integration Frameworks", in press Genome Research

joint project with Charles Cantor, Sequenom.

A new approach for gene prediction using multiple related genomes. The first evolutionary analysis of error based on evolutionary distance between organisms.

11. Y. Zheng, R. Roberts, S. Kasif, "Identification of the Adaptivity Layer of Microbial Organisms using Whole-Genome Variability Profiless", to be submitted, continued comparative genomics research with Rich Roberts on the structure of microbial organisms.

12*. N. O. Stitziel, J. Tseng, D. Pervouchine, D. Goddeau, S. Kasif, J. Liang, "Structural Location of Disease-Associated Single Nucleotide Polymorphisms", in press Journal of Molecular Biology.

A approach for classifying SNPs using a novel structural analysis tool and conservation analysis.

13*. J. Wu, Simon Kasif, and Charles DeLisi, "Identification of functional links between genes using phylogenetic profiles", in press Bioinformatics.

A rigorous methodology for assigning function based on phylogenetic profiles.

14*. D. Pervouchine, J. Graber and S. Kasif, "On the normalization of RNA equllibrium to sequence length", to appear NAR.

An efficient method for whole genome RNA analysis.

15. T. M. Murali and S. Kasif, "Discovering Conserved Gene Expression Motifs in Microarray Data", in review.

16. S. Letovsky, S. Kasif, "A Probabilistic Approach to Gene Function Assignment and Propagation in Protein Interaction Networks", in review.

A systematic approach for Functional Gene Annotation using Protein-Protein interaction graphs. 30-40% of genes in newly sequenced organisms have not been assigned function. This approach promises to be a breakthrough in functional annotation.

17. V. Pavlovic, J. Zhang, C. Cantor, S. Kasif, "The Effect of Evolution: on the Performance of Comparative Gene Finders" , in preparation.

20. M. Schaffer, J. Tullai, S. Kasif and G. Cooper, Cold Spring Harbor Meeting on System Biology.

21. Noga Alon, Richard Beigel and Simon Kasif and Steven Rudich and Benny Sudakov, "Learning a Hidden Matching", in review SIAM Journal of Computing.

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