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11 papers found.
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AUCpreD: proteome-level protein disorder prediction by AUC-maximized deep convolutional neural fields

Motivation: Protein intrinsically disordered regions (IDRs) play an important role in many biological processes. Two key properties of IDRs are (i) the occurrence is proteome-wide and (ii) the ratio of disordered residues is about 6%, which makes it challenging to accurately predict IDRs. Most IDR prediction methods use sequence profile to improve accuracy, which prevents its...

CMsearch: simultaneous exploration of protein sequence space and structure space improves not only protein homology detection but also protein structure prediction

Motivation: Protein homology detection, a fundamental problem in computational biology, is an indispensable step toward predicting protein structures and understanding protein functions. Despite the advances in recent decades on sequence alignment, threading and alignment-free methods, protein homology detection remains a challenging open problem. Recently, network methods that...

Protein contact prediction by integrating joint evolutionary coupling analysis and supervised learning

Motivation: Protein contact prediction is important for protein structure and functional study. Both evolutionary coupling (EC) analysis and supervised machine learning methods have been developed, making use of different information sources. However, contact prediction is still challenging especially for proteins without a large number of sequence homologs. Results: This article...

Exploiting ontology graph for predicting sparsely annotated gene function

Motivation: Systematically predicting gene (or protein) function based on molecular interaction networks has become an important tool in refining and enhancing the existing annotation catalogs, such as the Gene Ontology (GO) database. However, functional labels with only a few (<10) annotated genes, which constitute about half of the GO terms in yeast, mouse and human, pose a...

Fuzzy optimization for detecting enzyme targets of human uric acid metabolism

Motivation: Mathematical modeling and optimization have been used for detecting enzyme targets in human metabolic disorders. Such optimal drug design methods are generally differentiated as two stages, identification and decision-making, to find optimal targets. We developed a unified method named fuzzy equal metabolic adjustment to formulate an optimal enzyme target design...

Protein threading using context-specific alignment potential

Motivation: Template-based modeling, including homology modeling and protein threading, is the most reliable method for protein 3D structure prediction. However, alignment errors and template selection are still the main bottleneck for current template-base modeling methods, especially when proteins under consideration are distantly related. Results: We present a novel context...

A conditional neural fields model for protein threading

Motivation: Alignment errors are still the main bottleneck for current template-based protein modeling (TM) methods, including protein threading and homology modeling, especially when the sequence identity between two proteins under consideration is low (<30%). Results: We present a novel protein threading method, CNFpred, which achieves much more accurate sequence–template...

Alignment of distantly related protein structures: algorithm, bound and implications to homology modeling

Sheng Wang 0 Jian Peng 0 Jinbo Xu 0 Associate Editor: Anna Tramontano 0 Toyota Technological Institute at Chicago , IL 60637, USA Motivation: Building an accurate alignment of a large set of

Inference of biochemical network models in S-system using multiobjective optimization approach

Pang-Kai Liu 0 Feng-Sheng Wang 0 Associate Editor: John Quackenbush 0 Department of Chemical Engineering, National Chung Cheng University , Chiayi 621-02, Taiwan , ROC Motivation: The inference of

Evolutionary optimization with data collocation for reverse engineering of biological networks

Motivation: Modern experimental biology is moving away from analyses of single elements to whole-organism measurements. Such measured time-course data contain a wealth of information about the structure and dynamic of the pathway or network. The dynamic modeling of the whole systems is formulated as a reverse problem that requires a well-suited mathematical model and a very...

Haplotype reconstruction from SNP fragments by minimum error correction

Motivation: Haplotype reconstruction based on aligned single nucleotide polymorphism (SNP) fragments is to infer a pair of haplotypes from localized polymorphism data gathered through short genome fragment assembly. An important computational model of this problem is the minimum error correction (MEC) model, which has been mentioned in several literatures. The model retrieves a...