ISMB 2008 ISCB

16th Annual
International Conference
Intelligent Systems
for Molecular Biology


Metro Toronto Convention Centre (South Building)
Toronto, Canada


 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

















Accepted Posters
Category 'H'- Gene Prediction'
Poster H01
Genome-wide annotation of non-coding RNAs in Candida albicans: from in sillico prediction to validation
MariePier Scott-Boyer- Université de Montreal (IRIC)
Sébastien Lemieux (IRIC/Université de Montreal, -); Guillaume Bouvet (IRIC/Université de Montreal, -);
Short Abstract: This work presents the computational identification of non-coding RNAs in Candida albicans, an important fungal pathogen. The strategy used to find ncRNAs was to screen the genome with existing computational tools and to experimentally validate those predictions using a custom-built focused tiling DNA microarray.
Long Abstract: Click Here

Poster H02
GeneScan: A context independent gene finding program.
KOUSIK KUNDU- Centre for Cellular and Molecular Biology
No additional authors
Short Abstract: Computational gene finding is an open problem of high relevance. Many algorithms have been developed over the years, but most of them require a set of genes for training their program. Here we present an algorithm, GeneScan, which is context independent, robust to sequencing errors and fairly simple to implement.
Long Abstract: Click Here

Poster H03
Tiling array expression analysis shows the effects of ribonuclease deletion on non coding transcripts in yeast
Jules Gagnon- Univerty of Sherbrooke
Mona Wu (University of Sherbrooke, Microbiology and Infectiology); Sherif Abou Elela (University of Sherbrooke, Microbiology and Infectiology);
Short Abstract: A large number of non coding transcript of unknown function have been shown to be expressed in many genome. Here, we show that many of these transcripts are affected when some ribonucleases (RNT1 and RRP6) are inactivated in S. cerevisiae.
Long Abstract: Click Here

Poster H04
A Gene Structure Prediction Program Using Duration HMM
Hongseok Tae- SmallSoft. Co., Ltd
Kiejung Park (SmallSoft. Co., Ltd., );
Short Abstract: GeneChaser has been developed as a gene structure prediction program using a duration hidden Markov model. To estimate an optimal set of states, log odds scoring are used in GeneChaser's scoring modules and the probabilities of signal candidates are added in the computation of Viterbi algorithm.
Long Abstract: Click Here

Poster H05
Cancer discrimination based upon non-metric multidimensional scaling method
Masaru Konno- Chuo University
Yoshihiro Taguchi (Chuo University, physics);
Short Abstract: In the study of cancer, gene expression profile by DNA microarray turns out to be effective tools to discriminate patients' conditions which cannot be done in conventional pathology. In this study, we used nMDS and microarray data to discriminate cancer.
Long Abstract: Click Here

Poster H06
Improving SVR prediction of RNA minimum free energy z-score
Fernando Pineda- Johns Hopkins Bloomberg School of Public Health
Gang Wu (SAIC, NCI Center for Bioinformatics);
Short Abstract: We present a new SVM strategy for predicting the z-score of minimum free energy of RNA secondary structure. The new strategy improves upon published strategies, particularly on AT-rich sequences. The new strategy requires dramatically less training data and should be useful in RNA genefinders that make use of MFE z-score.
Long Abstract: Click Here

Poster H07
De novo Prediction of MicroRNAs using Hierarchical Hidden Markov Models
SABAH KADRI- CARNEGIE MELLON UNIVERSITY
Panayiotis Benos (Department of Computational Biology, University of Pittsburgh);
Short Abstract: We developed a novel Hierarchical HMM to predict microRNAs that utilizes structural and sequence-based information about microRNA precursors. We established a typical precursor template by summarizing microRNA registry data, which was used to develop the topology. We achieved a high accuracy but expect a substantial increase with better training sets.
Long Abstract: Click Here

Poster H09
tRNAscan-SE 2.0 and GtRNAdb: An extended approach for detecting and analyzing transfer RNA genes
Patricia Chan- University of California, Santa Cruz
Todd Lowe (University of California, Santa Cruz, School of Engineering);
Short Abstract: We describe a new version of tRNAscan-SE that improves memory efficiency and speed for detecting transfer RNAs in genomic sequence. Features include more accurate discrimination of tRNA identity and detection of atypical archaeal tRNAs. The tRNA annotations for more than 500 genomes are made available in the central repository GtRNAdb.
Long Abstract: Click Here

Poster H10
mGene: a novel discriminative gene finder
Gabriele Schweikert- MPI Tuebingen
Georg Zeller (MPI Tuebingen, FML); Alexander Zien (MPI Tuebingen, FML); Cheng Son Ong (MPI Tuebingen, FML); Fabio de Bona (MPI Tuebingen, FML); Soeren Sonnenburg (Fraunhofer FIRST, IDA); Petra Philips (MPI Tuebingen, FML); Gunnar Raetsch (MPI Tuebingen, FML);
Short Abstract: The acceleration of genome sequencing has put further emphasis on the need for
accurate computational gene finders. We present our improved system, mGene, which combines state-of-the-art structure prediction algorithms with SVM classifiers. As it performed excellent in the nGASP challenge, it was recently employed to annotate new nematode genomes.
Long Abstract: Click Here



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