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759
Improved prediction of signal peptides -- SignalP 3.0
- J. MOL. BIOL.
, 2004
"... We describe improvements of the currently most popular method for prediction of classically secreted proteins, SignalP. SignalP consists of two different predictors based on neural network and hidden Markov model algorithms, where both components have been updated. Motivated by the idea that the cle ..."
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Cited by 655 (7 self)
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We describe improvements of the currently most popular method for prediction of classically secreted proteins, SignalP. SignalP consists of two different predictors based on neural network and hidden Markov model algorithms, where both components have been updated. Motivated by the idea that the cleavage site position and the amino acid composition of the signal peptide are correlated, new features have been included as input to the neural network. This addition, combined with a thorough error-correction of a new data set, have improved the performance of the predictor significantly over SignalP version 2. In version 3, correctness of the cleavage site predictions have increased notably for all three organism groups, eukaryotes, Gram-negative and Grampositive bacteria. The accuracy of cleavage site prediction has increased in the range from 6-17 % over the previous version, whereas the signal peptide discrimination improvement is mainly due to the elimination of false positive predictions, as well as the introduction of a new discrimination score for the neural network. The new method has also been benchmarked against other available methods. Predictions can be made at the publicly available web server
Investigating semantic similarity measures across the Gene Ontology: the relationship between sequence and annotation
- Bioinformatics
, 2003
"... between sequence and annotation ..."
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The InterPro database, 2003 brings increased coverage and new features. Nucleic Acids Res
, 2003
"... InterPro, an integrated documentation resource of protein families, domains and functional sites, was created in 1999 as a means of amalgamating the major protein signature databases into one comprehensive resource. PROSITE, Pfam, PRINTS, ProDom, SMART and TIGRFAMs have been manually integrated and ..."
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Cited by 239 (17 self)
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InterPro, an integrated documentation resource of protein families, domains and functional sites, was created in 1999 as a means of amalgamating the major protein signature databases into one comprehensive resource. PROSITE, Pfam, PRINTS, ProDom, SMART and TIGRFAMs have been manually integrated and curated and are available in InterPro for text- and sequence-based searching. The results are provided in a single format that rationalises the results that would be obtained by searching the member databases individually. The latest release of
The InterPro database, an integrated documentation resource for protein families, domains and functional sites
- Nucleic Acids Res
"... ..."
Improving the Prediction of Protein Secondary Structure in Three and Eight Classes Using Recurrent Neural Networks and Profiles
, 2001
"... Secondarystructurepredictions areincreasinglybecomingtheworkhorseforseveralmethodsaimingatpredictingproteinstructure andfunction.Hereweuseensemblesofbidirectionalrecurrentneuralnetworkarchitectures, PSIBLAST -derivedprofiles,andalargenonredundant trainingsettoderivetwonewpredictors:(a)the secondvers ..."
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Cited by 214 (42 self)
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Secondarystructurepredictions areincreasinglybecomingtheworkhorseforseveralmethodsaimingatpredictingproteinstructure andfunction.Hereweuseensemblesofbidirectionalrecurrentneuralnetworkarchitectures, PSIBLAST -derivedprofiles,andalargenonredundant trainingsettoderivetwonewpredictors:(a)the secondversionoftheSSproprogramforsecondary structureclassificationintothreecategoriesand(b) thefirstversionoftheSSpro8programforsecondarystructureclassificationintotheeightclasses producedbytheDSSPprogram.Wedescribethe resultsofthreedifferenttestsetsonwhichSSpro achievedasustainedperformanceofabout78% correctprediction.Wereportconfusionmatrices, comparePSI-BLASTtoBLAST-derivedprofiles,and assessthecorrespondingperformanceimprovements. SSproandSSpro8areimplementedasweb servers,availabletogetherwithotherstructural featurepredictorsat:http://promoter.ics.uci.edu/ BRNN-PRED/.Proteins2002;47:228--235.
Prediction of the coding sequences of unidentified human genes. VI. The coding sequences of 80 new genes (KIAA0201KIAA0280) deduced by analysis of cDNA clones from cell line KG-1 and brain
- DNA Res
, 1996
"... In this series of projects of sequencing human cDNA clones which correspond to relatively long transcripts, we newly determined the entire sequences of 100 cDNA clones which were screened on the basis of the potentiality of coding for large proteins in vitro. The cDNA libraries used were the fractio ..."
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Cited by 185 (15 self)
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In this series of projects of sequencing human cDNA clones which correspond to relatively long transcripts, we newly determined the entire sequences of 100 cDNA clones which were screened on the basis of the potentiality of coding for large proteins in vitro. The cDNA libraries used were the fractions with average insert sizes from 5.3 to 7.0 kb of the size-fractionated cDNA libraries from human brain. The randomly sampled clones were single-pass sequenced from both the ends to select clones that are not registered in the public database. Then their protein-coding potentialities were examined by an in vitro transcription/translation system, and the clones that generated proteins larger than 60 kDa were entirely sequenced. Each clone gave a distinct open reading frame (ORF), and the length of the ORF was roughly coincident with the approximate molecular mass of the in vitro product estimated from its mobility on SDS-polyacrylamide gel electrophoresis. The average size of the cDNA clones sequenced was 6.1 kb, and that of the ORFs corresponded to 1200 amino acid residues. By computer-assisted analysis of the sequences with DNA and protein-motif databases (GenBank and PROSITE databases), the functions of at least 73% of the gene products could be anticipated, and 88 % of them (the products of 64 clones) were assigned to the functional categories of proteins relating to cell signaling/communication, nucleic acid managing,
Review: Protein Secondary Structure Prediction Continues to Rise
- J. Struct. Biol
, 2001
"... f prediction accuracy? We shall see. 2001 Academic Press INTRODUCTION History. Linus Pauling correctly guessed the formation of helices and strands (14, 15) (and falsely hypothesized other structures). Three years before Pauling's guess was verified by the publications of the first X-ray stru ..."
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Cited by 181 (22 self)
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f prediction accuracy? We shall see. 2001 Academic Press INTRODUCTION History. Linus Pauling correctly guessed the formation of helices and strands (14, 15) (and falsely hypothesized other structures). Three years before Pauling's guess was verified by the publications of the first X-ray structures (16, 17), one group had already ventured to predict secondary structure from sequence (18). The first-generation prediction methods following in the 1960s and 1970s were all based on single amino acid propensities (19). The second-generation methods dominating the scene until the early 1990s used propensities for segments of 3--51 adjacent residues (19). Basically any imaginable theoretical algorithm had been applied to the problem of predicting secondary structure from sequence. However, it seemed that prediction accuracy stalled at levels slightly above 60% (percentage of residues predicted correctly in one of the three states: helix, strand, and other). The reason for this limit was the
STRING: a database of predicted functional associations between proteins
- Nucleic Acids Res
, 2003
"... Functional links between proteins can often be inferred from genomic associations between the genes that encode them: groups of genes that are required for the same function tend to show similar species coverage, are often located in close proximity on the genome (in prokaryotes), and tend to be inv ..."
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Cited by 177 (12 self)
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Functional links between proteins can often be inferred from genomic associations between the genes that encode them: groups of genes that are required for the same function tend to show similar species coverage, are often located in close proximity on the genome (in prokaryotes), and tend to be involved in gene-fusion events. The database STRING is a precomputed global resource for the exploration and analysis of these associations. Since the three types of evidence differ conceptually, and the number of predicted interactions is very large, it is essential to be able to assess and compare the significance of individual predictions. Thus, STRING contains a unique scoring-framework based on benchmarks of the different types of associations against a common reference set, integrated in a single confidence score per prediction. The graphical representation of the network of inferred, weighted protein interactions provides a high-level view of functional linkage, facilitating the analysis of modularity in biological processes. STRING is updated continuously, and currently contains 261 033 orthologs in 89 fully sequenced genomes. The database predicts functional interactions at an expected level of accuracy of at least 80 % for more than half of the genes; it is online at
Accomplishments and Challenges in Literature Data Mining for Biology
, 2002
"... We review recent results in literature data mining for biology and discuss the need and the steps for a challenge evaluation for this field. Literature data mining has progressed from simple recognition of terms to extraction of interaction relationships from complex sentences, and has broadened fro ..."
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Cited by 164 (11 self)
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We review recent results in literature data mining for biology and discuss the need and the steps for a challenge evaluation for this field. Literature data mining has progressed from simple recognition of terms to extraction of interaction relationships from complex sentences, and has broadened from recognition of protein interactions to arange of problems such as improving homology search, identifying cellular location, and so on. To encourage participation and accelerate progress in this expanding field, we propose creating challenge evaluations, and we describe two specific applications in this context.
