ExPASy

ExPASy: the proteomics server for in-depth protein knowledge and analysis. The ExPASy (the Expert Protein Analysis System) World Wide Web server (http://www.expasy.org), is provided as a service to the life science community by a multidisciplinary team at the Swiss Institute of Bioinformatics (SIB). It provides access to a variety of databases and analytical tools dedicated to proteins and proteomics. ExPASy databases include SWISS-PROT and TrEMBL, SWISS-2DPAGE, PROSITE, ENZYME and the SWISS-MODEL repository. Analysis tools are available for specific tasks relevant to proteomics, similarity searches, pattern and profile searches, post-translational modification prediction, topology prediction, primary, secondary and tertiary structure analysis and sequence alignment. These databases and tools are tightly interlinked: a special emphasis is placed on integration of database entries with related resources developed at the SIB and elsewhere, and the proteomics tools have been designed to read the annotations in SWISS-PROT in order to enhance their predictions. ExPASy started to operate in 1993, as the first WWW server in the field of life sciences. In addition to the main site in Switzerland, seven mirror sites in different continents currently serve the user community.


References in zbMATH (referenced in 14 articles )

Showing results 1 to 14 of 14.
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  1. Bhardwaj, Swati; Gudur, Venkateshwarlu Yellaswamy; Acharyya, Amit: An accelerated computational approach in proteomics (2020)
  2. Liu, Yusha; Li, Meng; Morris, Jeffrey S.: Function-on-scalar quantile regression with application to mass spectrometry proteomics data (2020)
  3. Anupama, Rani; Lulu, Sajitha; Madhusmita, Rout; Vino, Sundararajan; Mukherjee, Amitava; Babu, Subramanian: Insights into the interaction of key biofilm proteins in \textitPseudomonasaeruginosa PAO1 with TiO(_2) nanoparticle: an \textitinsilico analysis (2019)
  4. Munir, Anum; Hussain, Shahid; Dilshad, Erum: Silver nanoparticles conjugated with neurotrophin 3 upregulate myelin gene transcription pathway (2018)
  5. Figueiredo Neto, Manoel; Figueiredo, Marxa L.: Skeletal muscle signal peptide optimization for enhancing propeptide or cytokine secretion (2016)
  6. Schleif, Frank-Michael; Tino, Peter: Indefinite proximity learning: a review (2015)
  7. Schleif, Frank-Michael; Zhu, Xibin; Hammer, Barbara: Sparse conformal prediction for dissimilarity data (2015)
  8. Nezafat, Navid; Ghasemi, Younes; Javadi, Gholamreza; Khoshnoud, Mohammad Javad; Omidinia, Eskandar: A novel multi-epitope peptide vaccine against cancer: an in silico approach (2014)
  9. Yu, Lezheng; Guo, Yanzhi; Li, Yizhou; Li, Gongbing; Li, Menglong; Luo, Jiesi; Xiong, Wenjia; Qin, Wenli: SecretP: identifying bacterial secreted proteins by fusing new features into Chou’s pseudo-amino acid composition (2010)
  10. Arakawa, Kazuharu; Tamaki, Satoshi; Kono, Nobuaki; Kido, Nobuhiro; Ikegami, Keita; Ogawa, Ryu; Tomita, Masaru: Genome projector: zoomable genome map with multiple views (2009) ioport
  11. Real-Chicharro, Alejandro; Mostazo, Iván Ruiz; Delgado, Ismael Navas; Kerzazi, Amine; Chniber, Othmane; Sánchez-Jiménez, Francisca; Medina, Miguel Angel; Montes, José Francisco Aldana: Protopia: a protein-protein interaction tool (2009) ioport
  12. Via, Allegra; Gould, Cathryn M.; Gemünd, Christine; Gibson, Toby J.; Helmer-Citterich, Manuela: A structure filter for the eukaryotic linear motif resource (2009) ioport
  13. Van der Linden, M. G.; Rêgo, T. G.; Araújo, D. A. M.; Farias, S. T.: Prediction of potential thermostable proteins in \textitXylellafastidiosa (2006)
  14. Gasteiger, Elisabeth; Gattiker, Alexandre; Hoogland, Christine; Ivanyi, Ivan; Appel, Ron D.; Bairoch, Amos: Expasy: The proteomics server for in-depth protein knowledge and analysis. (2003) ioport