Displaying publications 81 - 100 of 340 in total

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  1. Fulltext In Silico Approach for Characterization and Comparison of Repeats in the Genomes of Oil and Date Palms
    Filho JAF, de Brito LS, Leão AP, Alves AA, Formighieri EF, Júnior MTS
    Bioinform Biol Insights, 2017;11:1177932217702388.
    PMID: 28469420 DOI: 10.1177/1177932217702388
    Transposable elements (TEs) are mobile genetic elements present in almost all eukaryotic genomes. Due to their typical patterns of repetition, discovery, and characterization, they demand analysis by various bioinformatics software. Probably, as a result of the need for a complex analysis, many genomes publicly available do not have these elements annotated yet. In this study, a de novo and homology-based identification of TEs and microsatellites was performed using genomic data from 3 palm species: Elaeis oleifera (American oil palm, v.1, Embrapa, unpublished; v.8, Malaysian Palm Oil Board [MPOB], public), Elaeis guineensis (African oil palm, v.5, MPOB, public), and Phoenix dactylifera (date palm). The estimated total coverage of TEs was 50.96% (523 572 kb) and 42.31% (593 463 kb), 39.41% (605 015 kb), and 33.67% (187 361 kb), respectively. A total of 155 726 microsatellite loci were identified in the genomes of oil and date palms. This is the first detailed description of repeats in the genomes of oil and date palms. A relatively high diversity and abundance of TEs were found in the genomes, opening a range of further opportunities for applied research in these genera. The development of molecular markers (mainly simple sequence repeat), which may be immediately applied in breeding programs of those species to support the selection of superior genotypes and to enhance knowledge of the genetic structure of the breeding and natural populations, is the most notable opportunity.
    Matched MeSH terms: Computational Biology
  2. Fulltext Analysis of codon usage patterns and influencing factors in Nipah virus
    Chakraborty S, Deb B, Barbhuiya PA, Uddin A
    Virus Res, 2019 04 02;263:129-138.
    PMID: 30664908 DOI: 10.1016/j.virusres.2019.01.011
    Codon usage bias (CUB) is the unequal usage of synonymous codons of an amino acid in which some codons are used more often than others and is widely used in understanding molecular biology, genetics, and functional regulation of gene expression. Nipah virus (NiV) is an emerging zoonotic paramyxovirus that causes fatal disease in both humans and animals. NiV was first identified during an outbreak of a disease in Malaysia in 1998 and then occurred periodically since 2001 in India, Bangladesh, and the Philippines. We used bioinformatics tools to analyze the codon usage patterns in a genome-wide manner among 11 genomes of NiV as no work was reported yet. The compositional properties revealed that the overall GC and AT contents were 41.96 and 58.04%, respectively i.e. Nipah virus genes were AT-rich. Correlation analysis between overall nucleotide composition and its 3rd codon position suggested that both mutation pressure and natural selection might influence the CUB across Nipah genomes. Neutrality plot revealed natural selection might have played a major role while mutation pressure had a minor role in shaping the codon usage bias in NiV genomes.
    Matched MeSH terms: Computational Biology
  3. Fulltext Markers for genetic change
    Forcina G, Camacho-Sanchez M, Tuh FYY, Moreno S, Leonard JA
    Heliyon, 2021 Jan;7(1):e05583.
    PMID: 33437884 DOI: 10.1016/j.heliyon.2020.e05583
    Background and aims: Wildlife conservation has focused primarily on species for the last decades. Recently, popular perception and laws have begun to recognize the central importance of genetic diversity in the conservation of biodiversity. How to incorporate genetic diversity in ongoing monitoring and management of wildlife is still an open question.

    Methods: We tested a panel of multiplexed, high-throughput sequenced introns in the small mammal communities of two UNESCO World Heritage Sites on different continents to assess their viability for large-scale monitoring of genetic variability in a spectrum of diverse species. To enhance applicability across other systems, the bioinformatic pipeline for primer design was outlined.

    Results: The number of loci amplified and amplification evenness decreased as phylogenetic distance increased from the reference taxa, yet several loci were still variable across multiple mammal orders.

    Conclusions: Genetic variability found is informative for population genetic analyses and for addressing phylogeographic and phylogenetic questions, illustrated by small mammal examples here.

    Matched MeSH terms: Computational Biology
  4. Fulltext 16S rRNA Gene Sequencing for Deciphering the Colorectal Cancer Gut Microbiome: Current Protocols and Workflows
    Osman MA, Neoh HM, Ab Mutalib NS, Chin SF, Jamal R
    Front Microbiol, 2018;9:767.
    PMID: 29755427 DOI: 10.3389/fmicb.2018.00767
    The human gut holds the densest microbiome ecosystem essential in maintaining a healthy host physiology, whereby disruption of this ecosystem has been linked to the development of colorectal cancer (CRC). The advent of next-generation sequencing technologies such as the 16S rRNA gene sequencing has enabled characterization of the CRC gut microbiome architecture in an affordable and culture-free approach. Nevertheless, the lack of standardization in handling and storage of biospecimens, nucleic acid extraction, 16S rRNA gene primer selection, length, and depth of sequencing and bioinformatics analyses have contributed to discrepancies found in various published studies of this field. Accurate characterization of the CRC microbiome found in different stages of CRC has the potential to be developed into a screening tool in the clinical setting. This mini review aims to concisely compile all available CRC microbiome studies performed till end of 2016 and to suggest standardized protocols that are crucial in developing a gut microbiome screening panel for CRC.
    Matched MeSH terms: Computational Biology
  5. Fulltext Preliminary prediction of lipase 3D protein structure and function in Rhodococcus sp. NAM81 using bioinformatics approach
    Hasdianty Abdullah, Mohd Fadzli Ahmad, Farah Aula Mohd Fauzi, Nor Suhaila Yaacob, Abdul Latif Ibrahim
    Bioremediation Science and Technology Research, 2015;3(1):11-15.
    MyJurnal
    Protein function depends greatly on its structure. Based on this principle, it is vital to study the
    protein structure in order to understand its function. This study attempts to build the predicted
    model of lipase gene in Rhodococcus sp. NAM81 using homology modelling method. The
    predicted structure was then used to investigate the function of protein through several
    bioinformatic tools. The DNA sequence of lipase gene was obtained from the Rhodococcus sp.
    NAM81 genome scaffold. Blastx analysis showed 100% identity to the target enzyme andthe
    appropriate template for homology modelling was determined using Blastp analysis. The 3D
    protein structure was built using two homology modelling software, EsyPred3D and Swiss
    Model Server. Both structures built obtained LGScore of greater than 4, which means they are
    extremely good models according to ProQ validation criteria. Both structures also satisfied the
    Ramachandran plot structure validation analysis. The predicted structures were 100% matched
    with each other when superimposed with DaliLite pairwise. This shows that both structure
    validation servers agreed on the same model. Structure analysis using ProFunc had found seven
    motifs and active sites that indicate similar function of this protein with other known proteins.
    Thus, this study has successfully produced a good 3D protein structure for the target enzyme.
    Matched MeSH terms: Computational Biology
  6. Fulltext PalmXplore: oil palm gene database
    Sanusi NSNM, Rosli R, Halim MAA, Chan KL, Nagappan J, Azizi N, et al.
    Database (Oxford), 2018 01 01;2018.
    PMID: 30239681 DOI: 10.1093/database/bay095
    A set of Elaeis guineensis genes had been generated by combining two gene prediction pipelines: Fgenesh++ developed by Softberry and Seqping by the Malaysian Palm Oil Board. PalmXplore was developed to provide a scalable data repository and a user-friendly search engine system to efficiently store, manage and retrieve the oil palm gene sequences and annotations. Information deposited in PalmXplore includes predicted genes, their genomic coordinates, as well as the annotations derived from external databases, such as Pfam, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes. Information about genes related to important traits, such as those involved in fatty acid biosynthesis (FAB) and disease resistance, is also provided. The system offers Basic Local Alignment Search Tool homology search, where the results can be downloaded or visualized in the oil palm genome browser (MYPalmViewer). PalmXplore is regularly updated offering new features, improvements to genome annotation and new genomic sequences. The system is freely accessible at http://palmxplore.mpob.gov.my.
    Matched MeSH terms: Computational Biology
  7. Recent Development in Omics Studies
    Aizat WM, Ismail I, Noor NM
    Adv Exp Med Biol, 2018 11 2;1102:1-9.
    PMID: 30382565 DOI: 10.1007/978-3-319-98758-3_1
    The central dogma of molecular biology (DNA, RNA, protein and metabolite) has engraved our understanding of genetics in all living organisms. While the concept has been embraced for many decades, the development of high-throughput technologies particularly omics (genomics, transcriptomics, proteomics and metabolomics) has revolutionised the field to incorporate big data analysis including bioinformatics and systems biology as well as synthetic biology area. These omics approaches as well as systems and synthetic biology areas are now increasingly popular as seen by the growing numbers of publication throughout the years. Several journals which have published most of these related fields are also listed in this chapter to overview their impact and target journals.
    Matched MeSH terms: Computational Biology
  8. Fulltext Applications of Next-Generation Sequencing Technologies and Computational Tools in Molecular Evolution and Aquatic Animals Conservation Studies: A Short Review
    Tan MP, Wong LL, Razali SA, Afiqah-Aleng N, Mohd Nor SA, Sung YY, et al.
    Evol Bioinform Online, 2019;15:1176934319892284.
    PMID: 31839703 DOI: 10.1177/1176934319892284
    Aquatic ecosystems that form major biodiversity hotspots are critically threatened due to environmental and anthropogenic stressors. We believe that, in this genomic era, computational methods can be applied to promote aquatic biodiversity conservation by addressing questions related to the evolutionary history of aquatic organisms at the molecular level. However, huge amounts of genomics data generated can only be discerned through the use of bioinformatics. Here, we examine the applications of next-generation sequencing technologies and bioinformatics tools to study the molecular evolution of aquatic animals and discuss the current challenges and future perspectives of using bioinformatics toward aquatic animal conservation efforts.
    Matched MeSH terms: Computational Biology
  9. Combining Understanding of Immunological Mechanisms and Genetic Variants Toward Development of Personalized Medicine for Psoriasis Patients
    Gunter NV, Yap BJM, Chua CLL, Yap WH
    Front Genet, 2019;10:395.
    PMID: 31130981 DOI: 10.3389/fgene.2019.00395
    Psoriasis is multifactorial disease with complex genetic predisposition. Recent advances in genetics and genomics analyses have provided many insights into the relationship between specific genetic predisposition and the immunopathological mechanisms driving psoriasis manifestation. Novel approaches which utilize array-based genotyping technologies such as genome-wide association studies and bioinformatics tools for transcriptomics analysis have identified single nucleotide polymorphisms, genes and pathways that are associated with psoriasis. The discovery of these psoriasis-associated susceptibility loci, autoimmune targets and altered signaling pathways have provided opportunities to bridge the gap of knowledge from sequence to consequence, allowing new therapeutic strategies for the treatment of psoriasis to be developed. Here, we discuss recent advances in the field by highlighting how immune functions associated with psoriasis susceptibility loci may contribute to disease pathogenesis in different populations. Understanding the genetic variations in psoriasis and how these may influence the immunological pathways to cause disease will contribute to the efforts in developing novel and targeted personalized therapies for psoriasis patients.
    Matched MeSH terms: Computational Biology
  10. In silico identification and characterization of potential druggable targets among hypothetical proteins of Leptospira interrogans serovar Copenhageni: a comprehensive bioinformatics approach
    Siddiqui Q, Ali MSM, Leow ATC, Oslan SN, Mohd Shariff F
    J Biomol Struct Dyn, 2023 Dec;41(20):10347-10367.
    PMID: 36510668 DOI: 10.1080/07391102.2022.2154845
    Leptospirosis is one of the neglected zoonosis, affecting human and animal populations worldwide. Reliable effective therapeutics and concerns to look for more research into the molecular analysis of its genome is therefore needed. In the genomic pool of the Leptospira interrogans many hypothetical proteins are still uncharacterized. In the current research, we performed extensive in silico analysis to prioritize the potential hypothetical proteins of L. interrogans serovar Copenhageni via stepwise reducing the available hypothetical proteins (Total 3606) of the assembly to only 15, based on non-homologous to homosapien, essential, functional, virulent, cellular localization. Out of them, only two proteins WP_000898918.1 (Hypothetical Protein 1) & WP_001014594.1 (Hypothetical Protein 2) were found druggable and involved in protein-protein interaction network. The 3 D structures of these two target proteins were predicted via ab initio homology modeling followed by structures refinement and validation, as no structures were available till date. The analysis also revealed that the functional domains, families and protein-protein interacting partners identified in both proteins are crucial for the survival of the bacteria. The binding cavities were predicted for both the proteins through blind and specific protein-ligand docking with their respective ligands and inhibitors and were found to be in accordance with the druggable sites predicted by DoGSiteScorer. The docking interactions were found within the active functional domains for both the proteins while for Hypothetical Protein 2, the same residues were involved in interactions with Cytidine-5'-triphosphate in blind and specific docking. Furthermore, the simulations of molecular dynamics and free binding energy revealed the stable substrate binding and efficient binding energies, and were in accordance to our docking results. The work predicted two unique hypothetical proteins of L. interrogans as a potential druggable targets for designing of inhibitors for them.Communicated by Ramaswamy H. Sarma.
    Matched MeSH terms: Computational Biology
  11. Gene expression profiling of host lipid metabolism in SARS-CoV-2 infected patients: a systematic review and integrated bioinformatics analysis
    Munawar WASWA, Elias MH, Addnan FH, Hassandarvish P, AbuBakar S, Roslan N
    BMC Infect Dis, 2024 Jan 23;24(1):124.
    PMID: 38263024 DOI: 10.1186/s12879-024-08983-0
    BACKGROUND: The Coronavirus disease 2019 (COVID-19) pandemic occurred due to the dispersion of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Severe symptoms can be observed in COVID-19 patients with lipid-related comorbidities such as obesity and diabetes. Yet, the extensive molecular mechanisms of how SARS-CoV-2 causes dysregulation of lipid metabolism remain unknown.

    METHODS: Here, an advanced search of articles was conducted using PubMed, Scopus, EBSCOhost, and Web of Science databases using terms from Medical Subject Heading (MeSH) like SARS-CoV-2, lipid metabolism and transcriptomic as the keywords. From 428 retrieved studies, only clinical studies using next-generation sequencing as a gene expression method in COVID-19 patients were accepted. Study design, study population, sample type, the method for gene expression and differentially expressed genes (DEGs) were extracted from the five included studies. The DEGs obtained from the studies were pooled and analyzed using the bioinformatics software package, DAVID, to determine the enriched pathways. The DEGs involved in lipid metabolic pathways were selected and further analyzed using STRING and Cytoscape through visualization by protein-protein interaction (PPI) network complex.

    RESULTS: The analysis identified nine remarkable clusters from the PPI complex, where cluster 1 showed the highest molecular interaction score. Three potential candidate genes (PPARG, IFITM3 and APOBEC3G) were pointed out from the integrated bioinformatics analysis in this systematic review and were chosen due to their significant role in regulating lipid metabolism. These candidate genes were significantly involved in enriched lipid metabolic pathways, mainly in regulating lipid homeostasis affecting the pathogenicity of SARS-CoV-2, specifically in mechanisms of viral entry and viral replication in COVID-19 patients.

    CONCLUSIONS: Taken together, our findings in this systematic review highlight the affected lipid-metabolic pathways along with the affected genes upon SARS-CoV-2 invasion, which could be a potential target for new therapeutic strategies study in the future.

    Matched MeSH terms: Computational Biology
  12. Insights into the molecular mechanisms and signalling pathways of epithelial to mesenchymal transition (EMT) in colorectal cancer: A systematic review and bioinformatic analysis of gene expression
    Azizan S, Cheng KJ, Mejia Mohamed EH, Ibrahim K, Faruqu FN, Vellasamy KM, et al.
    Gene, 2024 Feb 20;896:148057.
    PMID: 38043836 DOI: 10.1016/j.gene.2023.148057
    Colorectal cancer (CRC) is ranked as the second leading cause of mortality worldwide, mainly due to metastasis. Epithelial to mesenchymal transition (EMT) is a complex cellular process that drives CRC metastasis, regulated by changes in EMT-associated gene expression. However, while numerous genes have been identified as EMT regulators through various in vivo and in vitro studies, little is known about the genes that are differentially expressed in CRC tumour tissue and their signalling pathway in regulating EMT. Using an integration of systematic search and bioinformatic analysis, gene expression profiles of CRC tumour tissues were compared to non-tumour adjacent tissues to identify differentially expressed genes (DEGs), followed by performing systematic review on common identified DEGs. Fifty-eight common DEGs were identified from the analysis of 82 tumour tissue samples obtained from four gene expression datasets (NCBI GEO). These DEGS were then systematically searched for their roles in modulating EMT in CRC based on previously published studies. Following this, 10 common DEGs (CXCL1, CXCL8, MMP1, MMP3, MMP7, TACSTD2, VIP, HPGD, ABCG2, CLCA4) were included in this study and subsequently subjected to further bioinformatic analysis. Their roles and functions in modulating EMT in CRC were discussed in this review. This study enhances our understanding of the molecular mechanisms underlying EMT and uncovers potential candidate genes and pathways that could be targeted in CRC.
    Matched MeSH terms: Computational Biology
  13. Fulltext MycoCAP - Mycobacterium Comparative Analysis Platform
    Choo SW, Ang MY, Dutta A, Tan SY, Siow CC, Heydari H, et al.
    Sci Rep, 2015 Dec 15;5:18227.
    PMID: 26666970 DOI: 10.1038/srep18227
    Mycobacterium spp. are renowned for being the causative agent of diseases like leprosy, Buruli ulcer and tuberculosis in human beings. With more and more mycobacterial genomes being sequenced, any knowledge generated from comparative genomic analysis would provide better insights into the biology, evolution, phylogeny and pathogenicity of this genus, thus helping in better management of diseases caused by Mycobacterium spp.With this motivation, we constructed MycoCAP, a new comparative analysis platform dedicated to the important genus Mycobacterium. This platform currently provides information of 2108 genome sequences of at least 55 Mycobacterium spp. A number of intuitive web-based tools have been integrated in MycoCAP particularly for comparative analysis including the PGC tool for comparison between two genomes, PathoProT for comparing the virulence genes among the Mycobacterium strains and the SuperClassification tool for the phylogenic classification of the Mycobacterium strains and a specialized classification system for strains of Mycobacterium abscessus. We hope the broad range of functions and easy-to-use tools provided in MycoCAP makes it an invaluable analysis platform to speed up the research discovery on mycobacteria for researchers. Database URL: http://mycobacterium.um.edu.my.
    Matched MeSH terms: Computational Biology/methods*
  14. In silico approaches for probiotic-derived bioactives
    Tan PL, Liong MT
    Trends Biotechnol, 2014 Dec;32(12):599-601.
    PMID: 25457386 DOI: 10.1016/j.tibtech.2014.09.011
    Matched MeSH terms: Computational Biology/methods*
  15. The complete mitogenome of the endangered white-clawed freshwater crayfish Austropotamobius pallipes (Lereboullet, 1858) (Crustacea: Decapoda: Astacidae)
    Grandjean F, Tan MH, Gan HY, Gan HM, Austin CM
    Mitochondrial DNA A DNA Mapp Seq Anal, 2016 09;27(5):3329-30.
    PMID: 25738217 DOI: 10.3109/19401736.2015.1018207
    The Austropotamobius pallipes complete mitogenome has been recovered using Next-Gen sequencing. Our sample of A. pallipes has a mitogenome of 15,679 base pairs (68.44% A + T content) made up of 13 protein-coding genes, 2 ribosomal subunit genes, 22 transfer RNAs, and a 877 bp non-coding AT-rich region. This is the first mitogenome sequenced for a crayfish from the family Astacidae and the 4(th) for northern hemisphere genera.
    Matched MeSH terms: Computational Biology/methods
  16. The complete mitogenome of the giant clam Tridacna squamosa (Heterodonta: Bivalvia: Tridacnidae)
    Gan HM, Gan HY, Tan MH, Penny SS, Willan RC, Austin CM
    Mitochondrial DNA A DNA Mapp Seq Anal, 2016 09;27(5):3220-1.
    PMID: 25648928 DOI: 10.3109/19401736.2015.1007355
    The complete mitochondrial genome of the commercially and ecologically important and internationally vulnerable giant clam Tridacna squamosa was recovered by genome skimming using the MiSeq platform. The T. squamosa mitogenome has 20,930 base pairs (62.35% A+T content) and is made up of 12 protein-coding genes, 2 ribosomal subunit genes, 24 transfer RNAs, and a 2594 bp non-coding AT-rich region. The mitogenome has a relatively large insertion in the atp6 gene. This is the first mitogenome to be sequenced from the genus Tridacna, and the family Tridacnidae and represents a new gene order.
    Matched MeSH terms: Computational Biology/methods
  17. Fulltext Differential Bees Flux Balance Analysis with OptKnock for in silico microbial strains optimization
    Choon YW, Mohamad MS, Deris S, Illias RM, Chong CK, Chai LE, et al.
    PLoS One, 2014;9(7):e102744.
    PMID: 25047076 DOI: 10.1371/journal.pone.0102744
    Microbial strains optimization for the overproduction of desired phenotype has been a popular topic in recent years. The strains can be optimized through several techniques in the field of genetic engineering. Gene knockout is a genetic engineering technique that can engineer the metabolism of microbial cells with the objective to obtain desirable phenotypes. However, the complexities of the metabolic networks have made the process to identify the effects of genetic modification on the desirable phenotypes challenging. Furthermore, a vast number of reactions in cellular metabolism often lead to the combinatorial problem in obtaining optimal gene deletion strategy. Basically, the size of a genome-scale metabolic model is usually large. As the size of the problem increases, the computation time increases exponentially. In this paper, we propose Differential Bees Flux Balance Analysis (DBFBA) with OptKnock to identify optimal gene knockout strategies for maximizing the production yield of desired phenotypes while sustaining the growth rate. This proposed method functions by improving the performance of a hybrid of Bees Algorithm and Flux Balance Analysis (BAFBA) by hybridizing Differential Evolution (DE) algorithm into neighborhood searching strategy of BAFBA. In addition, DBFBA is integrated with OptKnock to validate the results for improving the reliability the work. Through several experiments conducted on Escherichia coli, Bacillus subtilis, and Clostridium thermocellum as the model organisms, DBFBA has shown a better performance in terms of computational time, stability, growth rate, and production yield of desired phenotypes compared to the methods used in previous works.
    Matched MeSH terms: Computational Biology/methods*
  18. Computational epigenetic profiling of CpG islets in MTHFR
    Wei K, Sutherland H, Camilleri E, Haupt LM, Griffiths LR, Gan SH
    Mol Biol Rep, 2014 Dec;41(12):8285-92.
    PMID: 25213548 DOI: 10.1007/s11033-014-3729-x
    Computational epigenetics is a new area of research focused on exploring how DNA methylation patterns affect transcription factor binding that affect gene expression patterns. The aim of this study was to produce a new protocol for the detection of DNA methylation patterns using computational analysis which can be further confirmed by bisulfite PCR with serial pyrosequencing. The upstream regulatory element and pre-initiation complex relative to CpG islets within the methylenetetrahydrofolate reductase gene were determined via computational analysis and online databases. The 1,104 bp long CpG island located near to or at the alternative promoter site of methylenetetrahydrofolate reductase gene was identified. The CpG plot indicated that CpG islets A and B, within the island, contained 62 and 75 % GC content CpG ratios of 0.70 and 0.80-0.95, respectively. Further exploration of the CpG islets A and B indicates that the transcription start sites were GGC which were absent from the TATA boxes. In addition, although six PROSITE motifs were identified in CpG B, no motifs were detected in CpG A. A number of cis-regulatory elements were found in different regions within the CpGs A and B. Transcription factors were predicted to bind to CpGs A and B with varying affinities depending on the DNA methylation status. In addition, transcription factor binding may influence the expression patterns of the methylenetetrahydrofolate reductase gene by recruiting chromatin condensation inducing factors. These results have significant implications for the understanding of the architecture of transcription factor binding at CpG islets as well as DNA methylation patterns that affect chromatin structure.
    Matched MeSH terms: Computational Biology/methods*
  19. A context evaluation approach for structural comparison of proteins using cross entropy over n-gram modelling
    Razmara J, Deris SB, Parvizpour S
    Comput Biol Med, 2013 Oct;43(10):1614-21.
    PMID: 24034753 DOI: 10.1016/j.compbiomed.2013.07.022
    The structural comparison of proteins is a vital step in structural biology that is used to predict and analyse a new unknown protein function. Although a number of different techniques have been explored, the study to develop new alternative methods is still an active research area. The present paper introduces a text modelling-based technique for the structural comparison of proteins. The method models the secondary and tertiary structure of proteins in two linear sequences and then applies them to the comparison of two structures. The technique used for pairwise comparison of the sequences has been adopted from computational linguistics and its well-known techniques for analysing and quantifying textual sequences. To this end, an n-gram modelling technique is used to capture regularities between sequences, and then, the cross-entropy concept is employed to measure their similarities. Several experiments are conducted to evaluate the performance of the method and compare it with other commonly used programs. The assessments for information retrieval evaluation demonstrate that the technique has a high running speed, which is similar to other linear encoding methods, such as 3D-BLAST, SARST, and TS-AMIR, whereas its accuracy is comparable to CE and TM-align, which are high accuracy comparison tools. Accordingly, the results demonstrate that the algorithm has high efficiency compared with other state-of-the-art methods.
    Matched MeSH terms: Computational Biology/methods*
  20. Fulltext An efficient clustering algorithm for partitioning Y-short tandem repeats data
    Seman A, Bakar ZA, Isa MN
    BMC Res Notes, 2012;5:557.
    PMID: 23039132 DOI: 10.1186/1756-0500-5-557
    Y-Short Tandem Repeats (Y-STR) data consist of many similar and almost similar objects. This characteristic of Y-STR data causes two problems with partitioning: non-unique centroids and local minima problems. As a result, the existing partitioning algorithms produce poor clustering results.
    Matched MeSH terms: Computational Biology/methods*
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