INTRODUCTION This Web Service implements NetNES v. 1.1.ws0. It predicts leucine-rich nuclear export signals (NES) in eukaryotic proteins using a combination of neural networks and hidden Markov models. The method is described in detail in the following article: Analysis and prediction of leucine-rich nuclear export signals Tanja la Cour, Lars Kiemer, Anne Molgaard, Ramneek Gupta, Karen Skriver and Soren Brunak Protein Eng. Des. Sel., 17(6):527-36, 2004. Alongside this Web Service the NetNES method is also implemented as a traditional paste-and-click WWW server at: http://www.cbs.dtu.dk/services/NetNES/ The traditional server offers extended functionality and comprehensive documentation. It is suitable for close investigation of few proteins; this service is recommended for high throughput projects. 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 * 'sequenceRecord' answers to one sequence: * 'sequence' protein sequence. The sequence must be written using the one letter amino acid code in capital letters: `ACDEFGHIKLMNPQRSTVWY'.Other letters will be converted to `X' and treated as unknown amino acids. Other symbols, such as whitespace and numbers, will be ignored; * 'customNote' optional comment; * 'formalReference' * 'accession' unique identifier for the sequence. 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: * 'annotatedSequence' annotations - one element per input sequence; * 'sequenceRecord' answers to one sequence: * 'sequence' protein sequence given as an input; * 'formalReference' * 'accession' unique identifier for the input sequence; * 'annotation' * 'feature' * 'name' feature name, here always 'NetNES'; * 'occurence' occurence of a feature in a sequence; * 'position' always present, indicates the position of each residue; * 'point' residues number; * 'evidence' * 'predicted' * 'methodId' id composed of today's day, name and version of the method. Example: 6-4-2010NetNES-1.1ws0; * 'score' * 'type' = 'ANN' Artificial Neural Network (ANN) score type; * 'value' ANN prediction score value; * 'type' = 'HMM' Hidden Markov Model (HMM) score type; * 'value' HMM prediction score value; * 'type' = 'NES' NES score type - the main prediction score, calculated from ANN and HMM scores; * 'value' NES prediction score value; * 'verdict' contains 'Present' if the NES score exceeds the threshold, indicating that particular residue is expected to participate in a nuclear export signal. Otherwise contains 'Impossible'. Please note, that input and output data types of the NetNES v. 1.1.ws0 Web Service are defined by the external canonical XML-Schema - BioXSD. CONTACT Technical questions concerning the Web Service should go to Edita Bartaseviciute,edita@cbs.dtu.dk or Kristoffer Rapacki, rapacki@cbs.dtu.dk.