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107
A novel method of protein secondary structure prediction with high segment overlap measure: support vector machine approach
- J MOL BIOL
, 2001
"... We have introduced a new method of protein secondary structure prediction which is based on the theory of support vector machine (SVM). SVM represents a new approach to supervised pattern classification which has been successfully applied to a wide range of pattern recognition problems, including ob ..."
Abstract
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Cited by 177 (3 self)
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object recognition, speaker identification, gene function prediction with microarray expression profile, etc. In these cases, the performance of SVM either matches or is significantly better than that of traditional machine learning approaches, including neural networks. The first use of the SVM approach
Protein Function Prediction using Weak-label Learning
"... Protein function prediction is one of the fundamental issues in the post-genomic era. Multi-label learning is widely used for predicting functions of proteins. Most multi-label learning methods assume that the proteins with annotation do not have any missing functions. However, in practice, we may h ..."
Abstract
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Cited by 3 (2 self)
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have a subset of the ground-truth functions for a protein, and whether the protein has other functions is unknown. To complete the partial annotation of proteins, we propose a Protein Function Prediction method with W eaklabel Learning (ProWL), and a variant of ProWL (ProWL-IF). Both ProWL and Pro
Using Biological Networks in Protein Function Prediction and Gene Expression Analysis
"... While sequence homology search has been the main work horse in protein function prediction, it is not applicable to a significant portion of novel proteins that do not have informative homologs in sequence databases. Similarly, while statistical tests and learning algorithms based purely on gene exp ..."
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Cited by 1 (0 self)
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While sequence homology search has been the main work horse in protein function prediction, it is not applicable to a significant portion of novel proteins that do not have informative homologs in sequence databases. Similarly, while statistical tests and learning algorithms based purely on gene
Genome-wide survey for biologically functional pseudogenes
- PLoS Comput. Biol
, 2006
"... According to current estimates there exist about 20,000 pseudogenes in a mammalian genome. The vast majority of these are disabled and nonfunctional copies of protein-coding genes which, therefore, evolve neutrally. Recent findings that a Makorin1 pseudogene, residing on mouse Chromosome 5, is, inde ..."
Abstract
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Cited by 9 (0 self)
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1). Our approach is comparative and can be applied to any pair of species. It is implemented by a semi-automated pipeline based on cross-species BLAST comparisons and maximum-likelihood phylogeny estimations. To separate pseudogenes from protein-coding genes, we use standard methods, utilizing in
Protein Function Prediction with Incomplete Annotations
"... Abstract—Automated protein function prediction is one of the grand challenges in computational biology. Multi-label learning is widely used to predict functions of proteins. Most of multi-label learning methods make prediction for unlabeled proteins under the assump-tion that the labeled proteins ar ..."
Abstract
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Cited by 1 (0 self)
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Abstract—Automated protein function prediction is one of the grand challenges in computational biology. Multi-label learning is widely used to predict functions of proteins. Most of multi-label learning methods make prediction for unlabeled proteins under the assump-tion that the labeled proteins
Structural Learning of Genetic Regulatory Networks Based on Prior Biological Knowledge and Microarray Gene Expression Measurements
"... The reconstruction of genetic regulatory networks from microarray gene expression measurements has been a challenging problem in bioinformatics. Various methods have been proposed for this problem including the Bayesian Network (BN) approach. In this chapter we provide a comprehensive survey of the ..."
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The reconstruction of genetic regulatory networks from microarray gene expression measurements has been a challenging problem in bioinformatics. Various methods have been proposed for this problem including the Bayesian Network (BN) approach. In this chapter we provide a comprehensive survey
Survey of Programs Used to Detect Alternative Splicing Isoforms from Deep Sequencing Data In Silico
"... Next-generation sequencing techniques have been rapidly emerging. However, the massive sequencing reads hide a great deal of unknown important information. Advances have enabled researchers to discover alternative splicing (AS) sites and isoforms using computational approaches instead of molecular ..."
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experiments. Given the importance of AS for gene expression and protein diversity in eukaryotes, detecting alternative splicing and isoforms represents a hot topic in systems biology and epigenetics research. The computational methods applied to AS prediction have improved since the emergence of next
Finding groups in gene expression data
- J Biomed Biotechnol
"... The vast potential of the genomic insight offered by microarray technologies has led to their widespread use since they were introduced a decade ago. Application areas include gene function discovery, disease diagnosis, and inferring regulatory networks. Microarray experiments enable large-scale, h ..."
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Cited by 10 (0 self)
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of synthesis of proteins encoded by a gene or perhaps its involvement in a metabolic pathway. Differential expression between a control organism and an experimental or diseased organism can thus highlight genes whose function is related to the experimental challenge. An often cited example
Review Article Survey of Programs Used to Detect Alternative Splicing Isoforms from Deep Sequencing Data In Silico
"... Copyright © 2015 Feng Min et al.This is an open access article distributed under theCreative CommonsAttribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Next-generation sequencing techniques have been rapidly ..."
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expression and protein diversity in eukaryotes, detecting alternative splicing and isoforms represents a hot topic in systems biology and epigenetics research. The computational methods applied to AS prediction have improved since the emergence of next-generation sequencing. In this study, we introduce state
Massive functional mapping of a 5 0 -UTR by saturation mutagenesis, phenotypic sorting and deep sequencing
"... ABSTRACT We present here a method that enables functional screening of large number of mutations in a single experiment through the combination of random mutagenesis, phenotypic cell sorting and highthroughput sequencing. As a test case, we studied post-transcriptional gene regulation of the bacter ..."
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ABSTRACT We present here a method that enables functional screening of large number of mutations in a single experiment through the combination of random mutagenesis, phenotypic cell sorting and highthroughput sequencing. As a test case, we studied post-transcriptional gene regulation
Results 1 - 10
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107
