Expressed Sequence Tags (ESTs) provide a rapid and efficient approach for gene discovery and analysis of gene expression in eukaryotes. ESTs have also become particularly important with recent expanded efforts in complete genome sequencing of understudied, nonmodel eukaryotes such as protists and algae. For these projects, ESTs provide an invaluable source of data for gene identification and pr...

SoliD System chip-Seq Analysis The SOLiD System’s ability to generate over 400 million sequence tags (35 bp sequence reads) in a single run enables whole genome ChIP analysis of complex organisms. Sequence tags are mapped to a reference sequence and counted, to identify specific regions of protein binding. The ultra high throughput of the system provides researchers with the sensitivity and the...

Sequence-guided mining of metagenomic libraries provides a means of recovering specific natural product gene clusters of interest from the environment. In this study, we use ketosynthase gene (KS) PCR amplicon sequences (sequence tags) to explore the structural and biosynthetic diversities of pentangular polyphenols (PP). In phylogenetic analyses, eDNA-derived sequence tags often fall between c...

We present a computer program, termed V-SAGE (Virtual-SAGE), designed to facilitate the analysis of gene expression profiles by combining elements of SAGE (Serial Analysis of Gene Expression) with high-throughput EST analysis. The program re-iteratively correlates sequence tags adjacent to poly(A) tail sequence strings with a second or several tags located within the cDNA adjacent to the recogn...

This article describes a computational method to construct gene models by using evidence generated from a diverse set of sources, including those typical of a genome annotation pipeline. The program, called Combiner, takes as input a genomic sequence and the locations of gene predictions from ab initio gene finders, protein sequence alignments, expressed sequence tag and cDNA alignments, splice...

Identification of quantitative changes in gene expression that occur in the malignant mammary gland, if sufficiently characterized, may yield novel molecular markers which may be useful in the diagnosis and treatment of human breast cancer. Using modifications of a previously documented technique, the differential display polymerase chain reaction, we describe the isolation of differentially ex...

This report describes the application of Markov models to the problem of language-independent named entity recognition for the CoNLL-2002 shared task (Tjong Kim Sang, 2002). We approach the problem of identifying named entities as a kind of probabilistic tagging: given a sequence of words w1 : : :wn, we want to find the corresponding sequence of tags t1 : : : tn, drawn from a vocabulary of poss...

Sequence-based methods for transcriptome characterization have typically relied on generation of either serial analysis of gene expression tags or expressed sequence tags. Although such approaches have the potential to enumerate transcripts by counting sequence tags derived from them, they typically do not robustly survey the majority of transcripts along their entire length. Here we show that ...

BACKGROUND cDNA-Amplified Fragment Length Polymorphism (cDNA-AFLP) is a commonly used technique for genome-wide expression analysis that does not require prior sequence knowledge. Typically, quantitative expression data and sequence information are obtained for a large number of differentially expressed gene tags. However, most of the gene tags do not correspond to full-length (FL) coding seque...

We show that categories induced by unsupervised word clustering can surpass the performance of gold part-of-speech tags in dependency grammar induction. Unlike classic clustering algorithms, our method allows a word to have different tags in different contexts. In an ablative analysis, we first demonstrate that this context-dependence is crucial to the superior performance of gold tags — requir...