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 |
Accepted Posters |
View Posters By Category |
- A) Arrays
- B) Bioinformatics of Health and Disease
- C) Chemical and Pharmaceutical Informatics
- D) Comparative Genomics
- E) Databases
- F) Evolution
- G) Functional Genomics
- H) Gene Prediction
- I) Genome Annotation
- J) Genomics
- K) Interactions
- L) Machine Learning
- M) Population Genetics and Variation
- N) Proteomics
- O) Regulation
- P) Sequence Analysis
- Q) Structure and Function Prediction
- R) Systems Biology and Networks
- S) text mining
- T) Other (includes posters with fewer than 10 submissions)
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