Displaying publications 81 - 100 of 119 in total

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  1. Muniyandi RC, Zin AM, Sanders JW
    Biosystems, 2013 Dec;114(3):219-26.
    PMID: 24120990 DOI: 10.1016/j.biosystems.2013.09.008
    This paper presents a method to convert the deterministic, continuous representation of a biological system by ordinary differential equations into a non-deterministic, discrete membrane computation. The dynamics of the membrane computation is governed by rewrite rules operating at certain rates. That has the advantage of applying accurately to small systems, and to expressing rates of change that are determined locally, by region, but not necessary globally. Such spatial information augments the standard differentiable approach to provide a more realistic model. A biological case study of the ligand-receptor network of protein TGF-β is used to validate the effectiveness of the conversion method. It demonstrates the sense in which the behaviours and properties of the system are better preserved in the membrane computing model, suggesting that the proposed conversion method may prove useful for biological systems in particular.
    Matched MeSH terms: Computational Biology/methods*
  2. Kumar S
    BMC Res Notes, 2015;8:9.
    PMID: 25595103 DOI: 10.1186/s13104-015-0976-4
    Cytochrome P450s (CYPs) are important heme-containing proteins, well known for their monooxygenase reaction. The human cytochrome P450 4X1 (CYP4X1) is categorized as "orphan" CYP because of its unknown function. In recent studies it is found that this enzyme is expressed in neurovascular functions of the brain. Also, various studies have found the expression and activity of orphan human cytochrome P450 4X1 in cancer. It is found to be a potential drug target for cancer therapy. However, three-dimensional structure, the active site topology and substrate specificity of CYP4X1 remain unclear.
    Matched MeSH terms: Computational Biology/methods*
  3. 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*
  4. Mat-Sharani S, Firdaus-Raih M
    BMC Bioinformatics, 2019 Feb 04;19(Suppl 13):551.
    PMID: 30717662 DOI: 10.1186/s12859-018-2550-2
    BACKGROUND: Small open reading frames (smORF/sORFs) that encode short protein sequences are often overlooked during the standard gene prediction process thus leading to many sORFs being left undiscovered and/or misannotated. For many genomes, a second round of sORF targeted gene prediction can complement the existing annotation. In this study, we specifically targeted the identification of ORFs encoding for 80 amino acid residues or less from 31 fungal genomes. We then compared the predicted sORFs and analysed those that are highly conserved among the genomes.

    RESULTS: A first set of sORFs was identified from existing annotations that fitted the maximum of 80 residues criterion. A second set was predicted using parameters that specifically searched for ORF candidates of 80 codons or less in the exonic, intronic and intergenic sequences of the subject genomes. A total of 1986 conserved sORFs were predicted and characterized.

    CONCLUSIONS: It is evident that numerous open reading frames that could potentially encode for polypeptides consisting of 80 amino acid residues or less are overlooked during standard gene prediction and annotation. From our results, additional targeted reannotation of genomes is clearly able to complement standard genome annotation to identify sORFs. Due to the lack of, and limitations with experimental validation, we propose that a simple conservation analysis can provide an acceptable means of ensuring that the predicted sORFs are sufficiently clear of gene prediction artefacts.

    Matched MeSH terms: Computational Biology/methods*
  5. Dzayee SA, Khudhur PK, Mahmood A, Markov A, Maseleno A, Ebrahimpour Gorji A
    Anim Biotechnol, 2022 Nov;33(6):1359-1370.
    PMID: 33761829 DOI: 10.1080/10495398.2021.1899937
    Mastitis disease causes significant economic losses in dairy farms by reducing milk production, increasing production costs, and reducing milk quality. Streptococcus agalactiae continues to be a major cause of mastitis in dairy cattle. To date, there has been no approved multi-epitope vaccine against this pathogen in the market. In the present study, an efficient multi-epitope vaccine against S. agalactiae, the causative agent of mastitis, was designed using various immonoinformtics approaches. Potential epitopes were selected from Sip protein to improve vaccine immunogenicity. The designed vaccine is more antigenic in nature. Then, linkers and profilin adjuvant were added to enhance the immunity of vaccines. The designed vaccine was evaluated in terms of molecular weight, PI, immunogenicity, Toxicity, and allergenicity. Prediction of three-dimensional (3 D) structure of multi-epitope vaccine, followed by refinement and validation, was conducted to obtain a high-quality 3 D structure of the designed multi-epitope vaccine. The designed vaccine was then subjected to molecular docking with Toll-like receptor 11 (TLR11) receptor to evaluate its binding efficiency followed by dynamic simulation for stable interaction. In silico cloning approach was carried out to improve the expression of the vaccine construct. These analyses indicate that the designed multi-epitope vaccine may produce particular immune responses against S. agalactiae and may be further helpful to control mastitis after in vitro and in vivo immunological assays.
    Matched MeSH terms: Computational Biology/methods
  6. Kumar S, Fazil MHUT, Ahmad K, Tripathy M, Rajapakse JC, Verma NK
    Methods Mol Biol, 2019;1930:149-156.
    PMID: 30610609 DOI: 10.1007/978-1-4939-9036-8_18
    Analysis of protein-protein interactions is important for better understanding of molecular mechanisms involved in immune regulation and has potential for elaborating avenues for drug discovery targeting T-cell motility. Currently, only a small fraction of protein-protein interactions have been characterized in T-lymphocytes although there are several detection methods available. In this regard, computational approaches garner importance, with the continued explosion of genomic and proteomic data, for handling protein modeling and protein-protein interactions in large scale. Here, we describe a computational method to identify protein-protein interactions based on in silico protein design.
    Matched MeSH terms: Computational Biology/methods*
  7. Kaur H, Ahmad M, Scaria V
    Interdiscip Sci, 2016 Mar;8(1):95-101.
    PMID: 26298582 DOI: 10.1007/s12539-015-0273-x
    There is emergence of multidrug-resistant Salmonella enterica serotype typhi in pandemic proportions throughout the world, and therefore, there is a necessity to speed up the discovery of novel molecules having different modes of action and also less influenced by the resistance formation that would be used as drug for the treatment of salmonellosis particularly typhoid fever. The PhoP regulon is well studied and has now been shown to be a critical regulator of number of gene expressions which are required for intracellular survival of S. enterica and pathophysiology of disease like typhoid. The evident roles of two-component PhoP-/PhoQ-regulated products in salmonella virulence have motivated attempts to target them therapeutically. Although the discovery process of biologically active compounds for the treatment of typhoid relies on hit-finding procedure, using high-throughput screening technology alone is very expensive, as well as time consuming when performed on large scales. With the recent advancement in combinatorial chemistry and contemporary technique for compounds synthesis, there are more and more compounds available which give ample growth of diverse compound library, but the time and endeavor required to screen these unfocused massive and diverse library have been slightly reduced in the past years. Hence, there is demand to improve the high-quality hits and success rate for high-throughput screening that required focused and biased compound library toward the particular target. Therefore, we still need an advantageous and expedient method to prioritize the molecules that will be utilized for biological screens, which saves time and is also inexpensive. In this concept, in silico methods like machine learning are widely applicable technique used to build computational model for high-throughput virtual screens to prioritize molecules for advance study. Furthermore, in computational analysis, we extended our study to identify the common enriched structural entities among the biologically active compound toward finding out the privileged scaffold.
    Matched MeSH terms: Computational Biology/methods*
  8. Shahid M, Azfaralariff A, Law D, Najm AA, Sanusi SA, Lim SJ, et al.
    Sci Rep, 2021 01 15;11(1):1594.
    PMID: 33452398 DOI: 10.1038/s41598-021-81026-9
    Xanthorrhizol (XNT), is a bioactive compound found in Curcuma xanthorrhiza Roxb. This study aimed to determine the potential targets of the XNT via computational target fishing method. This compound obeyed Lipinski's and Veber's rules where it has a molecular weight (MW) of 218.37 gmol-1, TPSA of 20.23, rotatable bonds (RBN) of 4, hydrogen acceptor and donor ability is 1 respectively. Besides, it also has half-life (HL) values 3.5 h, drug-likeness (DL) value of 0.07, oral bioavailability (OB) of 32.10, and blood-brain barrier permeability (BBB) value of 1.64 indicating its potential as therapeutic drug. Further, 20 potential targets were screened out through PharmMapper and DRAR-CPI servers. Co-expression results derived from GeneMANIA revealed that these targets made connection with a total of 40 genes and have 744 different links. Four genes which were RXRA, RBP4, HSD11B1 and AKR1C1 showed remarkable co-expression and predominantly involved in steroid metabolic process. Furthermore, among these 20 genes, 13 highly expressed genes associated with xenobiotics by cytochrome P450, chemical carcinogenesis and steroid metabolic pathways were identified through gene ontology (GO) and KEGG pathway analysis. In conclusion, XNT is targeting multiple proteins and pathways which may be exploited to shape a network that exerts systematic pharmacological effects.
    Matched MeSH terms: Computational Biology/methods*
  9. Formenti G, Rhie A, Balacco J, Haase B, Mountcastle J, Fedrigo O, et al.
    Genome Biol, 2021 04 29;22(1):120.
    PMID: 33910595 DOI: 10.1186/s13059-021-02336-9
    BACKGROUND: Modern sequencing technologies should make the assembly of the relatively small mitochondrial genomes an easy undertaking. However, few tools exist that address mitochondrial assembly directly.

    RESULTS: As part of the Vertebrate Genomes Project (VGP) we develop mitoVGP, a fully automated pipeline for similarity-based identification of mitochondrial reads and de novo assembly of mitochondrial genomes that incorporates both long (> 10 kbp, PacBio or Nanopore) and short (100-300 bp, Illumina) reads. Our pipeline leads to successful complete mitogenome assemblies of 100 vertebrate species of the VGP. We observe that tissue type and library size selection have considerable impact on mitogenome sequencing and assembly. Comparing our assemblies to purportedly complete reference mitogenomes based on short-read sequencing, we identify errors, missing sequences, and incomplete genes in those references, particularly in repetitive regions. Our assemblies also identify novel gene region duplications. The presence of repeats and duplications in over half of the species herein assembled indicates that their occurrence is a principle of mitochondrial structure rather than an exception, shedding new light on mitochondrial genome evolution and organization.

    CONCLUSIONS: Our results indicate that even in the "simple" case of vertebrate mitogenomes the completeness of many currently available reference sequences can be further improved, and caution should be exercised before claiming the complete assembly of a mitogenome, particularly from short reads alone.

    Matched MeSH terms: Computational Biology/methods
  10. Yong HS, Song SL, Chua KO, Wayan Suana I, Eamsobhana P, Tan J, et al.
    Sci Rep, 2021 May 21;11(1):10680.
    PMID: 34021208 DOI: 10.1038/s41598-021-90162-1
    Spiders of the genera Nephila and Trichonephila are large orb-weaving spiders. In view of the lack of study on the mitogenome of these genera, and the conflicting systematic status, we sequenced (by next generation sequencing) and annotated the complete mitogenomes of N. pilipes, T. antipodiana and T. vitiana (previously N. vitiana) to determine their features and phylogenetic relationship. Most of the tRNAs have aberrant clover-leaf secondary structure. Based on 13 protein-coding genes (PCGs) and 15 mitochondrial genes (13 PCGs and two rRNA genes), Nephila and Trichonephila form a clade distinctly separated from the other araneid subfamilies/genera. T. antipodiana forms a lineage with T. vitiana in the subclade containing also T. clavata, while N. pilipes forms a sister clade to Trichonephila. The taxon vitiana is therefore a member of the genus Trichonephila and not Nephila as currently recognized. Studies on the mitogenomes of other Nephila and Trichonephila species and related taxa are needed to provide a potentially more robust phylogeny and systematics.
    Matched MeSH terms: Computational Biology/methods
  11. Rosli R, Amiruddin N, Ab Halim MA, Chan PL, Chan KL, Azizi N, et al.
    PLoS One, 2018;13(4):e0194792.
    PMID: 29672525 DOI: 10.1371/journal.pone.0194792
    Comparative genomics and transcriptomic analyses were performed on two agronomically important groups of genes from oil palm versus other major crop species and the model organism, Arabidopsis thaliana. The first analysis was of two gene families with key roles in regulation of oil quality and in particular the accumulation of oleic acid, namely stearoyl ACP desaturases (SAD) and acyl-acyl carrier protein (ACP) thioesterases (FAT). In both cases, these were found to be large gene families with complex expression profiles across a wide range of tissue types and developmental stages. The detailed classification of the oil palm SAD and FAT genes has enabled the updating of the latest version of the oil palm gene model. The second analysis focused on disease resistance (R) genes in order to elucidate possible candidates for breeding of pathogen tolerance/resistance. Ortholog analysis showed that 141 out of the 210 putative oil palm R genes had homologs in banana and rice. These genes formed 37 clusters with 634 orthologous genes. Classification of the 141 oil palm R genes showed that the genes belong to the Kinase (7), CNL (95), MLO-like (8), RLK (3) and Others (28) categories. The CNL R genes formed eight clusters. Expression data for selected R genes also identified potential candidates for breeding of disease resistance traits. Furthermore, these findings can provide information about the species evolution as well as the identification of agronomically important genes in oil palm and other major crops.
    Matched MeSH terms: Computational Biology/methods
  12. Hong KW, Asmah Hani AW, Nurul Aina Murni CA, Pusparani RR, Chong CK, Verasahib K, et al.
    Infect Genet Evol, 2017 Oct;54:263-270.
    PMID: 28711373 DOI: 10.1016/j.meegid.2017.07.015
    In this study, we report the comparative genomics and phylogenetic analysis of Corynebacterium diphtheriae strain B-D-16-78 that was isolated from a clinical specimen in 2016. The complete genome of C. diphtheriae strain B-D-16-78 was sequenced using PacBio Single Molecule, Real-Time sequencing technology and consists of a 2,474,151-bp circular chromosome with an average GC content of 53.56%. The core genome of C. diphtheriae was also deduced from a total of 74 strains with complete or draft genome sequences and the core genome-based phylogenetic analysis revealed close genetic relationship among strains that shared the same MLST allelic profile. In the context of CRISPR-Cas system, which confers adaptive immunity against re-invading DNA, 73 out of 86 spacer sequences were found to be unique to Malaysian strains which harboured only type-II-C and/or type-I-E-a systems. A total of 48 tox genes which code for the diphtheria toxin were retrieved from the 74 genomes and with the exception of one truncated gene, only nucleotide substitutions were detected when compared to the tox gene sequence of PW8. More than half were synonymous substitution and only two were nonsynonymous substitutions whereby H24Y was predicted to have a damaging effect on the protein function whilst T262V was predicted to be tolerated. Both toxigenic and non-toxigenic toxin-gene bearing strains have been isolated in Malaysia but the repeated isolation of toxigenic strains with the same MLST profile suggests the possibility of some of these strains may be circulating in the population. Hence, efforts to increase herd immunity should be continued and supported by an effective monitoring and surveillance system to track, manage and control outbreak of cases.
    Matched MeSH terms: Computational Biology/methods
  13. Abdullah-Zawawi MR, Ahmad-Nizammuddin NF, Govender N, Harun S, Mohd-Assaad N, Mohamed-Hussein ZA
    Sci Rep, 2021 10 04;11(1):19678.
    PMID: 34608238 DOI: 10.1038/s41598-021-99206-y
    Transcription factors (TFs) form the major class of regulatory genes and play key roles in multiple plant stress responses. In most eukaryotic plants, transcription factor (TF) families (WRKY, MADS-box and MYB) activate unique cellular-level abiotic and biotic stress-responsive strategies, which are considered as key determinants for defense and developmental processes. Arabidopsis and rice are two important representative model systems for dicot and monocot plants, respectively. A comprehensive comparative study on 101 OsWRKY, 34 OsMADS box and 122 OsMYB genes (rice genome) and, 71 AtWRKY, 66 AtMADS box and 144 AtMYB genes (Arabidopsis genome) showed various relationships among TFs across species. The phylogenetic analysis clustered WRKY, MADS-box and MYB TF family members into 10, 7 and 14 clades, respectively. All clades in WRKY and MYB TF families and almost half of the total number of clades in the MADS-box TF family are shared between both species. Chromosomal and gene structure analysis showed that the Arabidopsis-rice orthologous TF gene pairs were unevenly localized within their chromosomes whilst the distribution of exon-intron gene structure and motif conservation indicated plausible functional similarity in both species. The abiotic and biotic stress-responsive cis-regulatory element type and distribution patterns in the promoter regions of Arabidopsis and rice WRKY, MADS-box and MYB orthologous gene pairs provide better knowledge on their role as conserved regulators in both species. Co-expression network analysis showed the correlation between WRKY, MADs-box and MYB genes in each independent rice and Arabidopsis network indicating their role in stress responsiveness and developmental processes.
    Matched MeSH terms: Computational Biology/methods
  14. Sharko F, Rbbani G, Siriyappagouder P, Raeymaekers JAM, Galindo-Villegas J, Nedoluzhko A, et al.
    BMC Bioinformatics, 2023 May 19;24(1):205.
    PMID: 37208611 DOI: 10.1186/s12859-023-05331-y
    BACKGROUND: Circular RNAs (circRNAs) are covalently closed-loop RNAs with critical regulatory roles in cells. Tens of thousands of circRNAs have been unveiled due to the recent advances in high throughput RNA sequencing technologies and bioinformatic tools development. At the same time, polymerase chain reaction (PCR) cross-validation for circRNAs predicted by bioinformatic tools remains an essential part of any circRNA study before publication.

    RESULTS: Here, we present the CircPrime web-based platform, providing a user-friendly solution for DNA primer design and thermocycling conditions for circRNA identification with routine PCR methods.

    CONCLUSIONS: User-friendly CircPrime web platform ( http://circprime.elgene.net/ ) works with outputs of the most popular bioinformatic predictors of circRNAs to design specific circular RNA primers. CircPrime works with circRNA coordinates and any reference genome from the National Center for Biotechnology Information database).

    Matched MeSH terms: Computational Biology/methods
  15. Ranganathan S, Schönbach C, Nakai K, Tan TW
    BMC Genomics, 2010;11 Suppl 4:S1.
    PMID: 21143792 DOI: 10.1186/1471-2164-11-S4-S1
    The 2010 annual conference of the Asia Pacific Bioinformatics Network (APBioNet), Asia's oldest bioinformatics organisation formed in 1998, was organized as the 9th International Conference on Bioinformatics (InCoB), Sept. 26-28, 2010 in Tokyo, Japan. Initially, APBioNet created InCoB as forum to foster bioinformatics in the Asia Pacific region. Given the growing importance of interdisciplinary research, InCoB2010 included topics targeting scientists in the fields of genomic medicine, immunology and chemoinformatics, supporting translational research. Peer-reviewed manuscripts that were accepted for publication in this supplement, represent key areas of research interests that have emerged in our region. We also highlight some of the current challenges bioinformatics is facing in the Asia Pacific region and conclude our report with the announcement of APBioNet's 100 BioDatabases (BioDB100) initiative. BioDB100 will comply with the database criteria set out earlier in our proposal for Minimum Information about a Bioinformatics and Investigation (MIABi), setting the standards for biocuration and bioinformatics research, on which we will report at the next InCoB, Nov. 27 - Dec. 2, 2011 at Kuala Lumpur, Malaysia.
    Matched MeSH terms: Computational Biology/methods
  16. Sillitoe I, Bordin N, Dawson N, Waman VP, Ashford P, Scholes HM, et al.
    Nucleic Acids Res, 2021 Jan 08;49(D1):D266-D273.
    PMID: 33237325 DOI: 10.1093/nar/gkaa1079
    CATH (https://www.cathdb.info) identifies domains in protein structures from wwPDB and classifies these into evolutionary superfamilies, thereby providing structural and functional annotations. There are two levels: CATH-B, a daily snapshot of the latest domain structures and superfamily assignments, and CATH+, with additional derived data, such as predicted sequence domains, and functionally coherent sequence subsets (Functional Families or FunFams). The latest CATH+ release, version 4.3, significantly increases coverage of structural and sequence data, with an addition of 65,351 fully-classified domains structures (+15%), providing 500 238 structural domains, and 151 million predicted sequence domains (+59%) assigned to 5481 superfamilies. The FunFam generation pipeline has been re-engineered to cope with the increased influx of data. Three times more sequences are captured in FunFams, with a concomitant increase in functional purity, information content and structural coverage. FunFam expansion increases the structural annotations provided for experimental GO terms (+59%). We also present CATH-FunVar web-pages displaying variations in protein sequences and their proximity to known or predicted functional sites. We present two case studies (1) putative cancer drivers and (2) SARS-CoV-2 proteins. Finally, we have improved links to and from CATH including SCOP, InterPro, Aquaria and 2DProt.
    Matched MeSH terms: Computational Biology/methods
  17. Dawson NL, Sillitoe I, Lees JG, Lam SD, Orengo CA
    Methods Mol Biol, 2017;1558:79-110.
    PMID: 28150234 DOI: 10.1007/978-1-4939-6783-4_4
    This chapter describes the generation of the data in the CATH-Gene3D online resource and how it can be used to study protein domains and their evolutionary relationships. Methods will be presented for: comparing protein structures, recognizing homologs, predicting domain structures within protein sequences, and subclassifying superfamilies into functionally pure families, together with a guide on using the webpages.
    Matched MeSH terms: Computational Biology/methods*
  18. Zeti AM, Shamsir MS, Tajul-Arifin K, Merican AF, Mohamed R, Nathan S, et al.
    PLoS Comput Biol, 2009 Aug;5(8):e1000457.
    PMID: 19714208 DOI: 10.1371/journal.pcbi.1000457
    Matched MeSH terms: Computational Biology/methods*
  19. Ng CL, Lim TS, Choong YS
    Mol Biotechnol, 2024 Apr;66(4):568-581.
    PMID: 37742298 DOI: 10.1007/s12033-023-00885-x
    Since the advent of hybridoma technology in the year 1975, it took a decade to witness the first approved monoclonal antibody Orthoclone OKT39 (muromonab-CD3) in the year 1986. Since then, continuous strides have been made to engineer antibodies for specific desired effects. The engineering efforts were not confined to only the variable domains of the antibody but also included the fragment crystallizable (Fc) region that influences the immune response and serum half-life. Engineering of the Fc fragment would have a profound effect on the therapeutic dose, antibody-dependent cell-mediated cytotoxicity as well as antibody-dependent cellular phagocytosis. The integration of computational techniques into antibody engineering designs has allowed for the generation of testable hypotheses and guided the rational antibody design framework prior to further experimental evaluations. In this article, we discuss the recent works in the Fc-fused molecule design that involves computational techniques. We also summarize the usefulness of in silico techniques to aid Fc-fused molecule design and analysis for the therapeutics application.
    Matched MeSH terms: Computational Biology/methods
  20. Ong SY, Ng FL, Badai SS, Yuryev A, Alam M
    J Integr Bioinform, 2010;7(1).
    PMID: 20861532 DOI: 10.2390/biecoll-jib-2010-145
    Signal transduction through protein-protein interactions and protein modifications are the main mechanisms controlling many biological processes. Here we described the implementation of MedScan information extraction technology and Pathway Studio software (Ariadne Genomics Inc.) to create a Salmonella specific molecular interaction database. Using the database, we have constructed several signal transduction pathways in Salmonella enterica serovar Typhi which causes Typhoid Fever, a major health threat especially in developing countries. S. Typhi has several pathogenicity islands that control rapid switching between different phenotypes including adhesion and colonization, invasion, intracellular survival, proliferation, and biofilm formation in response to environmental changes. Understanding of the detailed mechanism for S. Typhi survival in host cells is necessary for development of efficient detection and treatment of this pathogen. The constructed pathways were validated using publically available gene expression microarray data for Salmonella.
    Matched MeSH terms: Computational Biology/methods*
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