Results 341 to 350 of about 9,720,197 (382)
Some of the next articles are maybe not open access.
Disease Gene Prediction by Integrating PPI Networks, Clinical RNA-Seq Data and OMIM Data
IEEE/ACM Transactions on Computational Biology & Bioinformatics, 2019Disease gene prediction is a challenging task that has a variety of applications such as early diagnosis and drug development. The existing machine learning methods suffer from the imbalanced sample issue because the number of known disease genes ...
Ping Luo +3 more
semanticscholar +1 more source
2008 International Symposium on Information Technology, 2008
With the increasingly popularity of genome sequencing, transforming such raw sequence data into knowledge remains a hard task. This project will develop an application for gene prediction using development tools such as Perl and PHP. The project will identify stretches of sequence for genomic DNA that is biologically functional including protein coding
Hazrina Yusof Hamdani +1 more
openaire +2 more sources
With the increasingly popularity of genome sequencing, transforming such raw sequence data into knowledge remains a hard task. This project will develop an application for gene prediction using development tools such as Perl and PHP. The project will identify stretches of sequence for genomic DNA that is biologically functional including protein coding
Hazrina Yusof Hamdani +1 more
openaire +2 more sources
Gene Annotation: Prediction and Testing
Annual Review of Genomics and Human Genetics, 2003Fifty years after the publication of DNA structure, the whole human genome sequence will be officially finished. This achievement marks the beginning of the task to catalogue every human gene and identify each of their function expression patterns. Currently, researchers estimate that there are about 30,000 human genes and approximately 70% of these ...
Jennifer L. Ashurst, John E. Collins
openaire +3 more sources
Gene prediction and gene classes in Arabidopsis thaliana
Journal of Biotechnology, 2000Gene prediction methods for eukaryotic genomes still are not fully satisfying. One way to improve gene prediction accuracy, proven to be relevant for prokaryotes, is to consider more than one model of genes. Thus, we used our classification of Arabidopsis thaliana genes in two classes (CU(1) and CU(2)), previously delineated according to statistical ...
Catherine Mathé +5 more
openaire +3 more sources
Computational Prediction of MicroRNA Genes
2013The computational identification of novel microRNA (miRNA) genes is a challenging task in bioinformatics. Massive amounts of data describing unknown functional RNA transcripts have to be analyzed for putative miRNA candidates with automated computational pipelines.
Jana Hertel +2 more
openaire +3 more sources
Incorrectly predicted genes in rice?
Gene, 2004Between one third and one half of the proposed rice genes appear to have no homologs in other species, including Arabidopsis. Compositional considerations, and a comparison of curated rice sequences with ex novo predictions, suggest that many or most of the putative genes without homologs may be false positive predictions, i.e., sequences that are ...
Giorgio Bernardi +3 more
openaire +3 more sources
2012
Evolutionary genomics is a field that relies heavily upon comparing genomes, that is, the full complement of genes of one species with another. However, given a genome sequence and little else, as is now often the case, genes must first be found and annotated before downstream analyses can be done.
openaire +2 more sources
Evolutionary genomics is a field that relies heavily upon comparing genomes, that is, the full complement of genes of one species with another. However, given a genome sequence and little else, as is now often the case, genes must first be found and annotated before downstream analyses can be done.
openaire +2 more sources
Science, 1999
Although cancer classification has improved over the past 30 years, there has been no general approach for identifying new cancer classes (class discovery) or for assigning tumors to known classes (class prediction).
Todd R. Golub +12 more
semanticscholar +1 more source
Although cancer classification has improved over the past 30 years, there has been no general approach for identifying new cancer classes (class discovery) or for assigning tumors to known classes (class prediction).
Todd R. Golub +12 more
semanticscholar +1 more source
2009
Most computational gene-finding methods in current use are derived from the fields of natural language processing and speech recognition. These latter fields are concerned with parsing spoken or written language into functional components such as nouns, verbs, and phrases of various types.
William H. Majoros +2 more
openaire +2 more sources
Most computational gene-finding methods in current use are derived from the fields of natural language processing and speech recognition. These latter fields are concerned with parsing spoken or written language into functional components such as nouns, verbs, and phrases of various types.
William H. Majoros +2 more
openaire +2 more sources
Sparse estimation of gene–gene interactions in prediction models
Statistical Methods in Medical Research, 2015Current assessment of gene–gene interactions is typically based on separate parallel analysis, where each interaction term is tested separately, while less attention has been paid on simultaneous estimation of interaction terms in a prediction model.
Erik Ingelsson +3 more
openaire +3 more sources