| Name | TMBETA-DISC |
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| Aliases | None |
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| Description | We have developed statistical and SVM based methods for discriminating beta barrel membrane proteins from amino acid sequence. The amino acid composition, residue pair preference and motifs are the major attributes for the program. 5 programs (TMBETADISC-COMP, TMBETADISC-DIPEPTIDE, TMBETADISC-MOTIF, TMBETADISC-SVM, TMBETADISC-RBF) was included in TMBETADISC (cited from the original site). |
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| Type | DB |
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| Main Institutes of management | Computational Biology Research Center (CBRC), National Institute of Advanced Industrial Science and Technology (AIST) |
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| Country of the Institute | Japan |
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| URL of the site | http://rbf.bioinfo.tw/~sachen/OMPpredict/TMBETADISC-RBF.php |
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| Interface | GUI |
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| Input example | Input example for TMBETADISC-RBF:Input amino acid sequences (FASTA-format) in the text box, push "submit" button. There is samples sequences on the down side of the top page. |
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| Keyword | SVM | amino acid composition | residue pair composition | motif composition | PSSM |
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| Amount of the all data for download（Mbyte） | Method to obtain the all data. | 0|None |
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| External resources (databases) in building the product. | None |
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| Data type | Protein-AminoAcid |
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| Biological species in the main concern | All species |
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| Conditions of use | None |
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| Frequency of updates (in last two years) | 0 |
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| Last date of updates (date of confirmation) | 2015/08/20 (2019/07/02) |
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| Main IDs used in the products | N/A |
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| How to make a link to get access to each IDs. | None |
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| external databases to which this database/tool have links | N/A |
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| Published papers (PubMed IDs) | pmid:18434251 | pmid:16204348 | pmid:15980447 | pmid:15833441 | pmid:15531602 |
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| Operational Status | Closed |
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