Franck Tanoh (almost 7 years ago)
firstname.lastname@example.org for details. WEB SERVICE OPERATION This Web Service is fully asynchronous; the usage is split into the following three operations: 1. runService Input:The following parameters and data: * ‘method’ – prediction method 0 for “C term 3.0”, 1 for “20S 3.0”; * ‘threshold’ – threshold for yes/no decision The default is 0.5; increasing the threshold results in better specificity, but worse sensitivity * ‘sequences’ – protein sequences, with unique identifiers The sequences must be written using the one letter amino acid code: `acdefghiklmnpqrstvwy’ or `ACDEFGHIKLMNPQRSTVWY’. Other letters will be converted to `X’ and treated as unknown amino acids. Other symbols, such as whitespace and numbers, will be ignored. Output: Unique job identifier 2. pollQueue Input:Unique job identifier Output: ‘jobstatus’ – the status of the job Possible values are QUEUED, ACTIVE, FINISHED, WAITING, REJECTED, UNKNOWN JOBID or QUEUE DOWN 3. fetchResult Input:Unique job identifier of a finished job Output: ‘output’ – prediction results For each input residue a record is output consisting of the following fields: seqname truncated to 10 characters in ver. 3.1a source “netchop-3.1a” (fixed string) feature “cleavage” (fixed string) start,end residue number (given twice) score prediction score strand,frame N/A comment answer (“S” for yes, “.” for no) CONTACT Questions concerning the scientific aspects of the NetChop method should go to Morten Nielsen, email@example.com; technical question concerning the Web Service should go to Peter Fischer Hallin, firstname.lastname@example.org or Kristoffer Rapacki, email@example.com.
Franck Tanoh(almost 7 years ago)
Predict cleavage sites of the human proteasome. interface: http://www.cbs.dtu.dk/services/NetChop/
The EMBRACE Registry (over 6 years ago)
NetChop produces neural network predictions for cleavage sites of the human proteasome. The method is described in detail in the following article:
The role of the proteasome in generating cytotoxic T cell epitopes: Insights obtained from improved predic
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