| URL: | http://www.caspur.it/ASPicDB/ |
| Full name: | Alternative Splicing Database |
| Description: | ASPicDB is a database of annotated transcript and protein variants generated by alternative splicing. |
| Year founded: | 2008 |
| Last update: | NA |
| Version: | v1.0 |
| Accessibility: |
Accessible
|
| Country/Region: | Italy |
| Data type: | |
| Data object: | |
| Database category: | |
| Major species: | |
| Keywords: |
| University/Institution: | University of Bologna |
| Address: | Bologna 40126,Italy |
| City: | Bologna |
| Province/State: | |
| Country/Region: | Italy |
| Contact name (PI/Team): | Graziano Pesole |
| Contact email (PI/Helpdesk): | graziano.pesole@biologia.uniba.it |
|
ASPicDB: a database web tool for alternative splicing analysis. [PMID: 25577391]
Alternative splicing (AS) is a basic molecular phenomenon that increases the functional complexity of higher eukaryotic transcriptomes. Indeed, through AS individual gene loci can generate multiple RNAs from the same pre-mRNA. AS has been investigated in a variety of clinical and pathological studies, such as the transcriptome regulation in cancer. In human, recent works based on massive RNA sequencing indicate that >95 % of pre-mRNAs are processed to yield multiple transcripts. Given the biological relevance of AS, several computational efforts have been done leading to the implementation of novel algorithms and specific specialized databases. Here we describe the web application ASPicDB that allows the recovery of detailed biological information about the splicing mechanism. ASPicDB provides powerful querying systems to interrogate AS events at gene, transcript, and protein levels. Finally, ASPicDB includes web visualization instruments to browse and export results for further off-line analyses. |
|
ASPicDB: a database of annotated transcript and protein variants generated by alternative splicing. [PMID: 21051348]
Alternative splicing is emerging as a major mechanism for the expansion of the transcriptome and proteome diversity, particularly in human and other vertebrates. However, the proportion of alternative transcripts and proteins actually endowed with functional activity is currently highly debated. We present here a new release of ASPicDB which now provides a unique annotation resource of human protein variants generated by alternative splicing. A total of 256,939 protein variants from 17,191 multi-exon genes have been extensively annotated through state of the art machine learning tools providing information of the protein type (globular and transmembrane), localization, presence of PFAM domains, signal peptides, GPI-anchor propeptides, transmembrane and coiled-coil segments. Furthermore, full-length variants can be now specifically selected based on the annotation of CAGE-tags and polyA signal and/or polyA sites, marking transcription initiation and termination sites, respectively. The retrieval can be carried out at gene, transcript, exon, protein or splice site level allowing the selection of data sets fulfilling one or more features settled by the user. The retrieval interface also enables the selection of protein variants showing specific differences in the annotated features. ASPicDB is available at http://www.caspur.it/ASPicDB/. |
|
ASPicDB: a database resource for alternative splicing analysis. [PMID: 18388144]
Alternative splicing has recently emerged as a key mechanism responsible for the expansion of transcriptome and proteome complexity in human and other organisms. Although several online resources devoted to alternative splicing analysis are available they may suffer from limitations related both to the computational methodologies adopted and to the extent of the annotations they provide that prevent the full exploitation of the available data. Furthermore, current resources provide limited query and download facilities. ASPicDB is a database designed to provide access to reliable annotations of the alternative splicing pattern of human genes and to the functional annotation of predicted splicing isoforms. Splice-site detection and full-length transcript modeling have been carried out by a genome-wide application of the ASPic algorithm, based on the multiple alignments of gene-related transcripts (typically a Unigene cluster) to the genomic sequence, a strategy that greatly improves prediction accuracy compared to methods based on independent and progressive alignments. Enhanced query and download facilities for annotations and sequences allow users to select and extract specific sets of data related to genes, transcripts and introns fulfilling a combination of user-defined criteria. Several tabular and graphical views of the results are presented, providing a comprehensive assessment of the functional implication of alternative splicing in the gene set under investigation. ASPicDB, which is regularly updated on a monthly basis, also includes information on tissue-specific splicing patterns of normal and cancer cells, based on available EST sequences and their library source annotation. www.caspur.it/ASPicDB |