CINECA IRIS Institutional Research Information System
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ItalianoDespite a fast-growing number of available plant genomes, available computational resources are poorly integrated and provide only limited access to the underlying data. Most existing databases focus on DNA/RNA data or specific gene families, with less emphasis on protein structure, function and variability. In particular, despite the economic importance of many plant accessions, there are no straightforward ways to retrieve or visualize information on their differences. To fill this gap, we developed PhytoTypeDB (http://phytotypedb.bio.unipd.it/), a scalable database containing plant protein annotations and genetic variants from resequencing of different accessions. The database content is generated by an integrated pipeline, exploiting state-of-the-art methods for protein characterization requiring only the proteome reference sequence and variant calling files. Protein names for unknown proteins are inferred by homology for over 95% of the entries. Single-nucleotide variants are visualized along with protein annotation in a user-friendly web interface. The server offers an effective querying system, which allows to compare variability among different species and accessions, to generate custom data sets based on shared functional features or to perform sequence searches. A documented set of exposed RESTful endpoints make the data accessible programmatically by third-party clients.
| Citation: | Necci, M.; Piovesan, D.; Micheletti, D.; Paladin, L.; Cestaro, A.; Tosatto, S.C.E. (2018). PhytoTypeDB: a database of plant protein inter-cultivar variability and function. DATABASE, 2018: 1-5. doi: 10.1093/database/bay125 handle: http://hdl.handle.net/10449/53417 |
| Internal authors: | Necci, Marco (First) |
| Organization unit: | Computational Biology # CRI_2011-JAN2016 |
| Authors: | Necci, M.; Piovesan, D.; Micheletti, D.; Paladin, L.; Cestaro, A.; Tosatto, S.C.E. |
| Title: | PhytoTypeDB: a database of plant protein inter-cultivar variability and function |
| Journal: | DATABASE |
| Issue Date: | 2018 |
| Scientific Disciplinary Area: | Settore BIO/11 - Biologia Molecolare |
| Language: | English |
| IF: | With Impact Factor ISI |
| Publication status: | Published |
| Nature of content: | Articolo in rivista/Article |
| Digital Object Identifier (DOI): | 10.1093/database/bay125 |
| Appears in Collections: | 01 - Journal article |
Files in This Item:
| File | Description | Type | License | |
|---|---|---|---|---|
| bay125.pdf | Versione editoriale |  | Open AccessView/Open |
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