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Results 1 - 10
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131
Improved Protein Secondary Structure Prediction Using Support Vector Machine With a New Encoding Scheme and an Advanced Tertiary Classifier
- IEEE Transactions on Nanobioscience
, 2004
"... Abstract—Prediction of protein secondary structures is an important problem in bioinformatics and has many applications. The recent trend of secondary structure prediction studies is mostly based on the neural network or the support vector machine (SVM). The SVM method is a comparatively new learnin ..."
Abstract
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Cited by 13 (3 self)
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Abstract—Prediction of protein secondary structures is an important problem in bioinformatics and has many applications. The recent trend of secondary structure prediction studies is mostly based on the neural network or the support vector machine (SVM). The SVM method is a comparatively new
Representation for Discovery of Protein Motifs
"... There are several dimensions and levels of com-plexity in which information on protein mo-tifs may be available. For example, one-dimensional sequence motifs may be associated with secondary structure identifiers. Alterna-tively, three-dimensional information on polypep-tide segments may be used to ..."
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to induce prototypical three-dimensional structure templates. This pa-per surveys various representations encountered in the protein motif discovery literature. Many of the representations are based on incompatible semantics, making difficult the comparison and combination of previous results. To make
Transcriptional and replicational activation functions in the bovine papillomavirus type 1 E2 protein are encoded by different structural determinants
- J Virol
, 1996
"... A set of E2 proteins with mutations in the amino-terminal transactivation domain was made by a scheme called clustered charged-to-alanine scan. These mutant E2 proteins were tested for expression, stability, and compartmentalization in cells and for sequence-specific DNA binding, as well as in funct ..."
Abstract
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Cited by 26 (5 self)
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A set of E2 proteins with mutations in the amino-terminal transactivation domain was made by a scheme called clustered charged-to-alanine scan. These mutant E2 proteins were tested for expression, stability, and compartmentalization in cells and for sequence-specific DNA binding, as well
Multivariate Analysis and Geovisualization with an Integrated Geographic Knowledge Discovery Approach." Cartography and Geographic Information Science 32(2
- Cartography and Geographic Information Science
, 2005
"... ABSTRACT: The discovery, interpretation, and presentation of multivariate spatial patterns are important for scientific understanding of complex geographic problems. This research integrates computational, visual, and cartographic methods together to detect and visualize multivariate spatial pattern ..."
Abstract
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Cited by 33 (11 self)
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ABSTRACT: The discovery, interpretation, and presentation of multivariate spatial patterns are important for scientific understanding of complex geographic problems. This research integrates computational, visual, and cartographic methods together to detect and visualize multivariate spatial
Smolign: A Spatial Motifs Based Protein Multiple Structural Alignment Method
"... Abstract—Availability of an effective tool for protein multiple structural alignment (MSTA) is essential for discovery and analysis of biologically significant structural motifs that can help solve functional annotation and drug design problems. Existing MSTA methods collect residue correspondences ..."
Abstract
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Cited by 1 (0 self)
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Abstract—Availability of an effective tool for protein multiple structural alignment (MSTA) is essential for discovery and analysis of biologically significant structural motifs that can help solve functional annotation and drug design problems. Existing MSTA methods collect residue correspondences
Accurate classification of protein structural families using coherent subgraph analysis
- In Proc. Pacific Symposium on Biocomputing
, 2004
"... Protein structural annotation and classification is an important problem in bioinformatics. We report on the development of an efficient subgraph mining technique and its application to finding characteristic substructural patterns within protein structural families. In our method, protein structure ..."
Abstract
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Cited by 30 (8 self)
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annotated in the SCOP database (Murzin et al, 1995). The Support Vector Machine algorithm was used to classify proteins from different families under the binary classification scheme. We find that this approach identifies spatial motifs unique to individual SCOP families and affords excellent discrimination
RESEARCH Mining the e spatially cohe
"... its functionality. Despite the large diversity in protein structures and functionality, it is amino acid residues, or between residues and other biomolecules, such as DNA. The complex three-dimensional structure. This spatial structure of a protein is an essential BioData Mining Meysman et al. BioDa ..."
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its functionality. Despite the large diversity in protein structures and functionality, it is amino acid residues, or between residues and other biomolecules, such as DNA. The complex three-dimensional structure. This spatial structure of a protein is an essential BioData Mining Meysman et al. Bio
ARTICLE Spatially encoded strategies in the execution of biomolecular-oriented 3D NMR experiments
"... Abstract Three-dimensional nuclear magnetic resonance (3D NMR) provides one of the foremost analytical tools available for the elucidation of biomolecular structure, function and dynamics. Executing a 3D NMR experiment generally involves scanning a series of time-domain signals S(t3), as a function ..."
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only been exemplified on model organic compounds. This publication discusses a number of strat-egies that could make these spatial encoding protocols compatible with 3D biomolecular NMR applications. These include a merging of 2D ultrafast NMR principles with temporal 2D encoding schemes, which can
Abstract MoBIoS: A Metric-Space DBMS to Support Biological Discovery 1
"... MoBIoS is a specialized database management system whose storage manager is based on metric-space indexing, and whose query language entails biological data types. When relational database management systems are used to support biological data, important data types are relegated to blob and unstruct ..."
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an abundance of bioinformatic discoveries that biological data is not random and exhibits interesting structure with respect to clustering. Just as Geographic Information Systems have been enabled by spatial databases, we argue that Biological Information Systems will be enabled by metric-space databases. We
Highly Accurate Protein Secondary Structure Prediction by Combination of n th-order Markov Transition Matrix and Support Vector Machine *
"... Motivation: Support Vector Machine (SVM) currently is a novel approach for protein secondary structure prediction. Based on statistical learning theory and its generalization, SVM was reported to have out-performed results for many applications on Bioinformatics. Even through the method of protein s ..."
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secondary structure prediction based on SVM achieved a good performance, it did not obviously produce the distinctively high results. The primary obstacle of previous prediction models that vastly inhibits the power of predicting algorithms is the inappropriately encoding scheme of protein sequence data
Results 1 - 10
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131
