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Ecoli Data Set Download: Data Folder, Data Set Description Abstract: This data contains protein localization sites |
Data Set Characteristics: | Multivariate | Number of Instances: | 336 | Area: | Life
Attribute Characteristics: | Real | Number of Attributes: | 8 | Date Donated | 1996-09-01
Associated Tasks: | Classification | Missing Values? | No | Number of Web Hits: | 53052
Source: Creator and Maintainer: Kenta Nakai Institue of Molecular and Cellular Biology Osaka, University 1-3 Yamada-oka, Suita 565 Japan nakai '@' imcb.osaka-u.ac.jp http://www.imcb.osaka-u.ac.jp/nakai/psort.html\ Donor: Paul Horton (paulh '@' cs.berkeley.edu) See also: yeast database Data Set Information: The references below describe a predecessor to this dataset and its development. They also give results (not cross-validated) for classification by a rule-based expert system with that version of the dataset. Reference: "Expert Sytem for Predicting Protein Localization Sites in Gram-Negative Bacteria", Kenta Nakai & Minoru Kanehisa, PROTEINS: Structure, Function, and Genetics 11:95-110, 1991. Reference: "A Knowledge Base for Predicting Protein Localization Sites in Eukaryotic Cells", Kenta Nakai & Minoru Kanehisa, Genomics 14:897-911, 1992. Attribute Information: 1. Sequence Name: Accession number for the SWISS-PROT database 2. mcg: McGeoch's method for signal sequence recognition. 3. gvh: von Heijne's method for signal sequence recognition. 4. lip: von Heijne's Signal Peptidase II consensus sequence score. Binary attribute. 5. chg: Presence of charge on N-terminus of predicted lipoproteins. Binary attribute. 6. aac: score of discriminant analysis of the amino acid content of outer membrane and periplasmic proteins. 7. alm1: score of the ALOM membrane spanning region prediction program. 8. alm2: score of ALOM program after excluding putative cleavable signal regions from the sequence. Relevant Papers: Paul Horton & Kenta Nakai. "A Probablistic Classification System for Predicting the Cellular Localization Sites of Proteins".Intelligent Systems in Molecular Biology, 109-115. St. Louis, USA 1996. [Web Link] Papers That Cite This Data Set1: Charles X. Ling and Qiang Yang and Jianning Wang and Shichao Zhang. Decision trees with minimal costs. ICML. 2004. [View Context]. Xiaoyong Chai and Li Deng and Qiang Yang and Charles X. Ling. Test-Cost Sensitive Naive Bayes Classification. ICDM. 2004. [View Context]. Vassilis Athitsos and Stan Sclaroff. Boosting Nearest Neighbor Classifiers for Multiclass Recognition. Boston University Computer Science Tech. Report No, 2004-006. 2004. [View Context]. Aik Choon Tan and David Gilbert. An Empirical Comparison of Supervised Machine Learning Techniques in Bioinformatics. APBC. 2003. [View Context]. Mukund Deshpande and George Karypis. Evaluation of Techniques for Classifying Biological Sequences. PAKDD. 2002. [View Context]. Huajie Zhang and Charles X. Ling. An Improved Learning Algorithm for Augmented Naive Bayes. PAKDD. 2001. [View Context]. Mark A. Hall. Department of Computer Science Hamilton, NewZealand Correlation-based Feature Selection for Machine Learning. Doctor of Philosophy at The University of Waikato. 1999. [View Context]. Paul Horton and Kenta Nakai. Better Prediction of Protein Cellular Localization Sites with the it k Nearest Neighbors Classifier. ISMB. 1997. [View Context]. . Prototype Selection for Composite Nearest Neighbor Classifiers. Department of Computer Science University of Massachusetts. 1997. [View Context]. Andrew Watkins and Jon Timmis and Lois C. Boggess. Artificial Immune Recognition System (AIRS): An ImmuneInspired Supervised Learning Algorithm. (abw5,jt6@kent.ac.uk) Computing Laboratory, University of Kent. [View Context]. Gaurav Marwah and Lois C. Boggess. Artificial Immune Systems for Classification : Some Issues. Department of Computer Science Mississippi State University. [View Context]. Chotirat Ann and Dimitrios Gunopulos. Scaling up the Naive Bayesian Classifier: Using Decision Trees for Feature Selection. Computer Science Department University of California. [View Context]. Citation Request: Please refer to the Machine Learning Repository's citation policy

[1] Papers were automatically harvested and associated with this data set, in collaboration with Rexa.info

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