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Benchmarking DNA methylation analysis of 14 alignment algorithms for whole genome bisulfite sequencing in mammals

COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL 2022年 20卷 4704-4716页

作者： Gong, Wentao Pan, Xiangchun Xu, Dantong Ji, Guanyu Wang, Yifei Tian, Yuhan Cai, Jiali Li, Jiaqi Zhang, Zhe Yuan, Xiaolong South China Agr Univ Coll Anim Sci Natl Engn Res Ctr Breeding Swine Ind Guangdong Lab Lingnan Modern AgrGuangdong Prov Ke Guangzhou 510642 Peoples R China Shenzhen Gendo Hlth Technol CO Ltd Shenzhen 518122 Peoples R China

Whole genome bisulfite sequencing (WGBS) is an essential technique for methylome studies. Although a series of tools have been developed to overcome the mapping challenges caused by bisulfite treatment, the latest available tools have not been evaluated on the performance of reads mapping as well as on bio-logical insights in multiple mammals. Herein, based on the real and simulated WGBS data of 14.77 billion reads, we undertook 936 mappings to benchmark and evaluate 14 wildly utilized alignment algorithms from reads mapping to biological interpretation in humans, cattle and pigs: Bwa-meth, BSBolt, BSMAP, Walt, Abismal, Batmeth2, Hisat_3n, Hisat_3n_repeat, Bismark-bwt2-e2e, Bismark-his2, BSSeeker2-bwt, BSSeeker2-soap2, BSSeeker2-bwt2-e2e and BSSeeker2-bwt2-local. Specifically, Bwa-meth, BSBolt, BSMAP, Bismark-bwt2-e2e and Walt exhibited higher uniquely mapped reads, mapped precision, recall and F1 score than other nine alignment algorithms, and the influences of distinct alignment algorithms on the methylomes varied considerably at the numbers and methylation levels of CpG sites, the calling of differentially methylated CpGs (DMCs) and regions (DMRs). Moreover, we reported that BSMAP showed the highest accuracy at the detection of CpG coordinates and methylation levels, the calling of DMCs, DMRs, DMR-related genes and signaling pathways. These results suggested that careful selection of algo-rithms to profile the genome-wide DNA methylation is required, and our works provided investigators with useful information on the choice of alignment algorithms to effectively improve the DNA methyla-tion detection accuracy in mammals.(c) 2022 The Author(s). Published by Elsevier B.V. on behalf of Research Network of Computational and Structural Biotechnology. This is an open access article under the CC BY-NC-ND license (http://***/licenses/by-nc-nd/4.0/).

关键词： alignment algorithms Comparative methylomes Mammals Whole genome bisulfite sequencing

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Impact of alignment algorithms on 16S metagenomics analysis 8

Impact of alignment algorithms on 16S metagenomics analysis

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8th Cairo International Biomedical Engineering Conference (CIBEC)

作者： Mysara, Mohamed Ramakrishnan, Akshaya Shahin, Mona Monsieurs, Pieter Belgian Nucl Res Ctr SCK CEN Microbiol Unit Mol Belgium Antwerp Univ Lab Med Microbiol Antwerp Belgium Nile Univ Giza Egypt

ISBN: (纸本)9781509029877

The development of high-throughput sequencing technologies has provided microbial ecologists with an efficient approach to assess bacterial diversity at an unseen depth. In the last year, various platforms have been used for such analysis particularly the IIIumina MiSeq, 454 pyrosequencing GS FLX+ and PacBio sequencing platforms. However, analysing such high-throughput data is posing important computational challenges, requiring specialized bioinformatics solutions ending with clustering those sequences into Operational Taxonomic Units (OTUs). Individual algorithms grappling with each of those challenges and numerous efforts have been put to compare them. Nonetheless, there is a need to elucidate the effect of the alignment strategy and subsequently the distance calculation on the OTU-clustering. In this work, a comparative analysis between various alignment algorithms in respect to the produced OTUs is performed. These results suggest that multiple sequence alignment driven distances, particularly those incorporating the secondary structure, are more accurate than pairwise alignment approaches. Additionally, disregarding the computation burden, the de novo multiple sequence aligners are superior to reference based aligners.

关键词： Operational Taxonomic Units 16S metagenomics alignment algorithms Secondary structure

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GLAlign: A Novel Algorithm for Local Network alignment

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IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS 2019年第6期16卷 1958-1969页

作者： Milano, Marianna Guzzi, Pietro Hiram Cannataro, Mario Magna Graecia Univ Catanzaro Dept Med & Surg Sci Data Analyt Res Ctr I-88100 Catanzaro CZ Italy

Networks are successfully used as a modelling framework in many application domains. For instance, Protein-Protein Interaction Networks (PPINs) model the set of interactions among proteins in a cell. A critical application of network analysis is the comparison among PPINs of different organisms to reveal similarities among the underlying biological processes. algorithms for comparing networks (also referred to as network aligners) fall into two main classes: global aligners, which aim to compare two networks on a global scale, and local aligners that aim to evidence single sub-regions of similarity among networks. The possibility to improve the performance of the aligners by mixing the two approaches is a growing research area. In our previous work, we started to explore the possibility to use global alignment to improve the local one. We here explore further this possibility by using topological information extracted from global alignment to guide the steps of the local alignment. Therefore, we present Global Local Aligner (GLAlign), a methodology that improves the performances of local network aligners by exploiting a preliminary global alignment. Furthermore, we provide implementation of GLAlign. As a proof-of-principle, we evaluated the performance of the GLAlign prototype on the PPINs of five species. Results show that GLAlign methodology outperforms the state-of-the-arts local alignment algorithms.

关键词： alignment algorithms local alignment global alignment PPI network GLAlign

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On Complexity of Protein Structure alignment Problem under Distance Constraint

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IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS 2012年第2期9卷 511-516页

作者： Poleksic, Aleksandar Univ No Iowa Dept Comp Sci Cedar Falls IA 50614 USA

We study the well-known Largest Common Point-set (LCP) under Bottleneck Distance Problem. Given two proteins a and b (as sequences of points in three-dimensional space) and a distance cutoff sigma, the goal is to find a spatial superposition and an alignment that maximizes the number of pairs of points from a and b that can be fit under the distance sigma from each other. The best to date algorithms for approximate and exact solution to this problem run in time O(n(8)) and O(n(32) ), respectively, where n represents protein length. This work improves runtime of the approximation algorithm and the expected runtime of the algorithm for absolute optimum for both order-dependent and order-independent alignments. More specifically, our algorithms for near-optimal and optimal sequential alignments run in time O(n(7) log n) and O(n(14) log n), respectively. For nonsequential alignments, corresponding running times are O(n(7.5)) and O(n(14.5)).

关键词： Protein structure structural alignment structural similarity alignment algorithms

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A PROTEIN alignment SCORING SYSTEM SENSITIVE AT ALL EVOLUTIONARY DISTANCES

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JOURNAL OF MOLECULAR EVOLUTION 1993年第3期36卷 290-300页

作者： ALTSCHUL, SF 1. National Center for Biotechnology Information National Library of Medicine National Institutes of Health 20894 Bethesda MD USA

Protein sequence alignments generally are constructed with the aid of a ''substitution matrix'' that specifies a score for aligning each pair of amino acids. Assuming a simple random protein model, it can be shown that any such matrix, when used for evaluating variable-length local alignments, is implicitly a ''log-odds'' matrix, with a specific probability distribution for amino acid pairs to which it is uniquely tailored. Given a model of protein evolution from which such distributions may be derived, a substitution matrix adapted to detecting relationships at any chosen evolutionary distance can be constructed. Because in a database search it generally is not known a priori what evolutionary distances will characterize the similarities found, it is necessary to employ an appropriate range of matrices in order not to overlook potential homologies. This paper formalizes this concept by defining a scoring system that is sensitive at all detectable evolutionary distances. The statistical behavior of this scoring system is analyzed, and it is shown that for a typical protein database search, estimating the originally unknown evolutionary distance appropriate to each alignment costs slightly over two bits of information, or somewhat less than a factor of five in statistical significance. A much greater cost may be incurred, however, if only a single substitution matrix, corresponding to the wrong evolutionary distance, is employed.

关键词： HOMOLOGY SEQUENCE COMPARISON STATISTICAL SIGNIFICANCE alignment algorithms PATTERN RECOGNITION

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STRUCTFAST: Protein sequence remote homology detection and alignment using novel dynamic programming and profile-profile scoring

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PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS 2006年第4期64卷 960-967页

作者： Debe, Derek A. Danzer, Joseph F. Goddard, William A., III Poleksic, Aleksandar Univ No Iowa Dept Comp Sci Cedar Falls IA 50614 USA Eidogen Sertanty Inc San Diego CA 92121 USA CALTECH Mat & Proc Simulat Ctr Pasadena CA 91106 USA

STRUCTFAST is a novel profile-profile alignment algorithm capable of detecting weak similarities between protein sequences. The increased sensitivity and accuracy of the STRUM FAST method are achieved through several unique features. First, the algorithm utilizes a novel dynamic programming engine capable of incorporating important information from a structural family directly into the alignment process. Second, the algorithm employs a rigorous analytical formula for profile-profile scoring to overcome the limitations of ad hoc scoring functions that require adjustable parameter training. Third, the algorithm employs Convergent Island Statistics (CIS) to compute the statistical significance of alignment scores independently for each pair of sequences. STRUCTFAST routinely produces alignments that meet or exceed the quality obtained by an expert human homology modeler, as evidenced by its performance in the latest CAFASP4 and CASP6 blind prediction benchmark experiments.

关键词： protein structure homology modeling comparative modeling alignment algorithms alignment statistics

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A first approach to CLIR using character n-grams alignment

A first approach to CLIR using character n-grams alignment

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7th Workshop of the Cross-Language Evaluation Forum

作者： Vilares, Jesus Oakes, Michael P. Tait, John I. Univ A Coruna Dept Computac Campus Elvina S-N La Coruna 15071 Spain Univ Sunderland Sch Comp & Technol Sunderland Durham England

ISBN: (纸本)9783540749981

This paper describes the technique for translation of character n-grams we developed for our participation in CLEF 2006. This solution avoids the need for word normalization during indexing or translation, and it can also deal with out-of- vocabulary words. Since it does not rely on language- specific processing, it can be applied to very different languages, even when linguistic information and resources are scarce or unavailable. Our proposal makes considerable use of freely available resources and also tries to achieve a higher speed during the n-gram alignment process with respect to other similar approaches.

关键词： cross-language information retrieval character n-grams translation algorithms alignment algorithms association measures

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Detecting Non-Trivial Protein Structure Relationships

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CURRENT BIOINFORMATICS 2016年第2期11卷 234-242页

作者： Poleksic, Aleksandar Univ No Iowa Dept Comp Sci 305 ITTC Cedar Falls IA 50614 USA

Automated methods for protein three-dimensional structure comparison play an important role in understanding protein function, evolution and biochemical reaction mechanisms. Since the tertiary structure of proteins is more conserved than their amino-acid sequences, accurately aligning three-dimensional structures allows to detect homology between proteins in the "twilight zone", those sharing less than similar to 25% sequence identity. Unfortunately, existing methods for protein structure comparison are often unable to properly compare and align proteins related by complex structural modifications, such as circular permutations, large conformational changes and large residue insertions and deletions. In this paper, we present an algorithm capable of computing biologically meaningful alignments from structurally homologous but spatially distant fragments. Accurate alignments of proteins that have undergone large conformational variations are derived from multiple spatial superpositions. For mild to moderate conformational variations, approximate rigid body superpositions are recursively relaxed to allow matching of spatially distant regions. The algorithm incorporates an exact procedure for computing alignments of proteins related by circular permutations. We used two benchmarking datasets to demonstrate that our algorithm compares favorably to some of the most accurate methods available today. In the most difficult RIPC test set, the median accuracy of our method is 100%. The algorithm is freely available as a Web service at http://***.

关键词： alignment algorithms protein structure structure comparison structural alignment

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Compression and approximate matching

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COMPUTER JOURNAL 1999年第1期42卷 1-10页

作者： Allison, L Powell, D Dix, TI Monash Univ Sch Comp Sci & Software Engn Clayton Vic 3168 Australia

A population of sequences is called non-random if there is a statistical model and an associated compression algorithm that allows members of the population to be compressed, on average. Any available statistical model of a population should be incorporated into algorithms for alignment of the sequences and doing so changes the rank order of possible alignments in general. The model should also be used in deciding if a resulting approximate match between two sequences is significant or not. It is shown how to do this for two plausible interpretations involving pairs of sequences that might or might not be related. Efficient alignment algorithms are described for quite general statistical models of sequences. The new alignment algorithms are more sensitive to what might be termed 'features' of the sequences. A natural significance test is shown to be rarely fooled by apparent similarities between two sequences that are merely typical of all or most members of the population, even unrelated members.

关键词： Image compression Pattern matching Character recognition algorithms Statistical methods Approximate matching alignment algorithms Longest common subsequence Pattern matching Image compression Sequence alignment compression approximate match Character recognition Statistical methods statistical models (nuclear) Compression algorithms Sequences alignment Data compression algorithms Rank order

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PERFORMANCE EVALUATION OF AMINO-ACID SUBSTITUTION MATRICES

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PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS 1993年第1期17卷 49-61页

作者： HENIKOFF, S HENIKOFF, JG Howard Hughes Medical Institute Basic Sciences Division Fred Hutchinson Cancer Research Center Seattle Washington 98104

Several choices of amino acid substitution matrices are currently available for searching and alignment applications. These choices were evaluated using the BLAST searching program, which is extremely sensitive to differences among matrices, and the Prosite catalog, which lists members of hundreds of protein families. Matrices derived directly from either sequence-based or structure-based alignments of distantly related proteins performed much better overall than extrapolated matrices based on the Dayhoff evolutionary model. Similar results were obtained with the FASTA searching program. Improved performance appears to be general rather than family-specific, reflecting improved accuracy in scoring alignments. An implementation of a multiple matrix strategy was also tested. While no combination of three matrices performed as well as the single best matrix, BLOSUM 62, good results were obtained using a combination of sequence-based and structure-based matrices. This hybrid set of matrices is likely to be useful in certain situations. Our results illustrate the importance of matrix selection and the value of a comprehensive approach to evaluation of protein comparison tools. (C) 1993 Wiley-Liss, Inc.

关键词： HOMOLOGY SEARCHING MUTATION DATA MATRIX AMINO ACID SEQUENCE alignment algorithms DATABASE SEARCHING

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