{"title":"TransMem:在Excel电子表格中实现的神经网络,用于预测蛋白质的跨膜结构域。","authors":"P Aloy, J Cedano, B Oliva, F X Avilés, E Querol","doi":"10.1093/bioinformatics/13.3.231","DOIUrl":null,"url":null,"abstract":"<p><strong>Motivation: </strong>Genomic sequences from different organisms, even prokaryotic, have plenty of orphan ORFs, making necessary methods for the prediction of protein structure and function. The prediction of the presence of hydrophobic transmembrane (HTM) stretches is a valuable clue for this.</p><p><strong>Results: </strong>The program. TransMem, based on a neural network and running on personal computers (either Apple Macintosh or PC, using Excel worksheets), for the prediction and distribution of amino acid residues in transmembrane segments of integral membrane proteins is reported. The percentage of residue predictive accuracy obtained for the set of proteins tested is 93%, ranging from 99.9% for the best to 71.7% for the worst prediction. The segment-based accuracy is 93.6%; 63.6% of the protein set match any of the predicted and observed segment locations.</p><p><strong>Availability: </strong>TransMem is available upon request or by anonymous up: IP address: luz.uab.es, directory/pub/ TransMem. It is also placed on the EMBL file server (ftp:/(/)ftp.ebi.ac.uk/pub/software/mac/TransMem ).</p>","PeriodicalId":77081,"journal":{"name":"Computer applications in the biosciences : CABIOS","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"1997-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1093/bioinformatics/13.3.231","citationCount":"24","resultStr":"{\"title\":\"'TransMem': a neural network implemented in Excel spreadsheets for predicting transmembrane domains of proteins.\",\"authors\":\"P Aloy, J Cedano, B Oliva, F X Avilés, E Querol\",\"doi\":\"10.1093/bioinformatics/13.3.231\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Motivation: </strong>Genomic sequences from different organisms, even prokaryotic, have plenty of orphan ORFs, making necessary methods for the prediction of protein structure and function. The prediction of the presence of hydrophobic transmembrane (HTM) stretches is a valuable clue for this.</p><p><strong>Results: </strong>The program. TransMem, based on a neural network and running on personal computers (either Apple Macintosh or PC, using Excel worksheets), for the prediction and distribution of amino acid residues in transmembrane segments of integral membrane proteins is reported. The percentage of residue predictive accuracy obtained for the set of proteins tested is 93%, ranging from 99.9% for the best to 71.7% for the worst prediction. The segment-based accuracy is 93.6%; 63.6% of the protein set match any of the predicted and observed segment locations.</p><p><strong>Availability: </strong>TransMem is available upon request or by anonymous up: IP address: luz.uab.es, directory/pub/ TransMem. It is also placed on the EMBL file server (ftp:/(/)ftp.ebi.ac.uk/pub/software/mac/TransMem ).</p>\",\"PeriodicalId\":77081,\"journal\":{\"name\":\"Computer applications in the biosciences : CABIOS\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1997-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1093/bioinformatics/13.3.231\",\"citationCount\":\"24\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Computer applications in the biosciences : CABIOS\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1093/bioinformatics/13.3.231\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computer applications in the biosciences : CABIOS","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1093/bioinformatics/13.3.231","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 24
摘要
动机:来自不同生物,甚至原核生物的基因组序列都有大量的孤儿orf,这为预测蛋白质结构和功能提供了必要的方法。预测疏水跨膜(HTM)拉伸的存在是一个有价值的线索。结果:程序。TransMem基于神经网络,在个人电脑(苹果Macintosh或个人电脑,使用Excel工作表)上运行,用于预测完整膜蛋白跨膜段氨基酸残基的分布。对一组被测试的蛋白质获得的残基预测准确率百分比为93%,从最佳预测的99.9%到最差预测的71.7%不等。基于分段的准确率为93.6%;63.6%的蛋白质组与预测和观察到的片段位置相匹配。可用性:TransMem可根据请求或匿名访问:IP地址:luz.uab.es,目录/pub/ TransMem。它也放在EMBL文件服务器(ftp:/(/)ftp.ebi.ac)上。英国/ pub /软件/ mac / TransMem)。
'TransMem': a neural network implemented in Excel spreadsheets for predicting transmembrane domains of proteins.
Motivation: Genomic sequences from different organisms, even prokaryotic, have plenty of orphan ORFs, making necessary methods for the prediction of protein structure and function. The prediction of the presence of hydrophobic transmembrane (HTM) stretches is a valuable clue for this.
Results: The program. TransMem, based on a neural network and running on personal computers (either Apple Macintosh or PC, using Excel worksheets), for the prediction and distribution of amino acid residues in transmembrane segments of integral membrane proteins is reported. The percentage of residue predictive accuracy obtained for the set of proteins tested is 93%, ranging from 99.9% for the best to 71.7% for the worst prediction. The segment-based accuracy is 93.6%; 63.6% of the protein set match any of the predicted and observed segment locations.
Availability: TransMem is available upon request or by anonymous up: IP address: luz.uab.es, directory/pub/ TransMem. It is also placed on the EMBL file server (ftp:/(/)ftp.ebi.ac.uk/pub/software/mac/TransMem ).