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1.  Deep insights into Dictyocaulus viviparus transcriptomes provides unique prospects for new drug targets and disease intervention 
Biotechnology advances  2010;29(3):10.1016/j.biotechadv.2010.11.005.
The lungworm, Dictyocaulus viviparus, causes parasitic bronchitis in cattle, and is responsible for substantial economic losses in temperate regions of the world. Here, we undertake the first large-scale exploration of available transcriptomic data for this lungworm, examine differences in transcription between different stages/both genders and identify and prioritize essential molecules linked to fundamental metabolic pathways, which could represent novel drug targets. Approximately 3 million expressed sequence tags (ESTs), generated by 454 sequencing from third-stage larvae (L3) as well as adult females and males of D. viviparus, were assembled and annotated. The assembly of these sequences yielded ~61,000 contigs, of which relatively large proportions encoded collagens (4.3%), ubiquitins (2.1%) and serine/threonine protein kinases (1.9%). Subtractive analysis in silico identified 6,928 nucleotide sequences as being uniquely transcribed in L3, and 5,203 and 7,889 transcripts as being exclusive to the adult female and male, respectively. Most peptides predicted from the conceptual translations were nucleoplasmins (L3), serine/threonine protein kinases (female) and major sperm proteins (male). Additional analyses allowed the prediction of three drug target candidates, whose Caenorhabditis elegans homologues were linked to a lethal RNA interference phenotype. This detailed exploration, combined with future transcriptomic sequencing of all developmental stages of D. viviparus, will facilitate future investigations of the molecular biology of this parasitic nematode as well as genomic sequencing. These advances will underpin the discovery of new drug and/or vaccine targets, focused on biotechnological outcomes.
doi:10.1016/j.biotechadv.2010.11.005
PMCID: PMC3827682  PMID: 21182926
Dictyocaulus viviparous; Bovine lungworm; Next-generation sequencing; Bioinformatics; Transcriptome; Ancylostoma-secreted proteins; Drug target prediction
2.  InCoB2013 introduces Systems Biology as a major conference theme 
BMC Systems Biology  2013;7(Suppl 3):S1.
The Asia-Pacific Bioinformatics Network (APBioNet) held the first International Conference on Bioinformatics (InCoB) in Bangkok in 2002 to promote North-South networking. Commencing as a forum for Asia-Pacific researchers to interact with and learn from with scientists of developed countries, InCoB has become a major regional bioinformatics conference, with participants from the region as well as North America and Europe. Since 2006, InCoB has selected the best submissions for publication in BMC Bioinformatics. In response to the growth and maturation of data-driven approaches, InCoB added BMC Genomics in 2009 and with the introduction of this conference supplement, BMC Systems Biology to its journal choices for submitting authors. Co-hosting InCoB2013 with the second International Conference for Translational Bioinformatics (ICTBI) is in line with InCoB's support for the current trend in taking bioinformatics to the bedside, along with a systems approach to solving biological problems.
doi:10.1186/1752-0509-7-S3-S1
PMCID: PMC3816296  PMID: 24555777
3.  APBioNet—Transforming Bioinformatics in the Asia-Pacific Region 
PLoS Computational Biology  2013;9(10):e1003317.
doi:10.1371/journal.pcbi.1003317
PMCID: PMC3814852  PMID: 24204244
4.  Simple re-instantiation of small databases using cloud computing 
BMC Genomics  2013;14(Suppl 5):S13.
Background
Small bioinformatics databases, unlike institutionally funded large databases, are vulnerable to discontinuation and many reported in publications are no longer accessible. This leads to irreproducible scientific work and redundant effort, impeding the pace of scientific progress.
Results
We describe a Web-accessible system, available online at http://biodb100.apbionet.org, for archival and future on demand re-instantiation of small databases within minutes. Depositors can rebuild their databases by downloading a Linux live operating system (http://www.bioslax.com), preinstalled with bioinformatics and UNIX tools. The database and its dependencies can be compressed into an ".lzm" file for deposition. End-users can search for archived databases and activate them on dynamically re-instantiated BioSlax instances, run as virtual machines over the two popular full virtualization standard cloud-computing platforms, Xen Hypervisor or vSphere. The system is adaptable to increasing demand for disk storage or computational load and allows database developers to use the re-instantiated databases for integration and development of new databases.
Conclusions
Herein, we demonstrate that a relatively inexpensive solution can be implemented for archival of bioinformatics databases and their rapid re-instantiation should the live databases disappear.
doi:10.1186/1471-2164-14-S5-S13
PMCID: PMC3852246  PMID: 24564380
Database archival; Re-instantiation; Cloud computing; BioSLAX; biodb100; MIABi
5.  First transcriptomic analysis of the economically important parasitic nematode, Trichostrongylus colubriformis, using a next-generation sequencing approach 
Trichostrongylus colubriformis (Strongylida), a small intestinal nematode of small ruminants, is a major cause of production and economic losses in many countries. The aims of the present study were to define the transcriptome of the adult stage of T. colubriformis, using 454 sequencing technology and bioinformatic analyses, and to predict the main pathways that key groups of molecules are linked to in this nematode. A total of 21,259 contigs were assembled from the sequence data produced from a normalized cDNA library; 7,876 of these contigs had known orthologues in the free-living nematode Caenorhabditis elegans, and encoded, amongst others, proteins with ‘transthyretin-like’ (8.8%), ‘RNA recognition’ (8.4%) and ‘metridin-like ShK toxin’ (7.6%) motifs. Bioinformatic analyses inferred that relatively high proportions of the C. elegans homologues are involved in biological pathways linked to ‘peptidases’ (4%), ‘ribosome’ (3.6%) and ‘oxidative phosphorylation’ (3%). Highly represented were peptides predicted to be associated with the nervous system, digestion of host proteins or inhibition of host proteases. Probabilistic functional gene networking of the complement of C. elegans orthologues (n = 2,126) assigned significance to particular subsets of molecules, such as protein kinases and serine/threonine phosphatases. The present study represents the first, comprehensive insight into the transcriptome of adult T. colubriformis, which provides a foundation for fundamental studies of the molecular biology and biochemistry of this parasitic nematode as well as prospects for identifying targets for novel nematocides. Future investigations should focus on comparing the transcriptomes of different developmental stages, both genders and various tissues of this parasitic nematode for the prediction of essential genes/gene products that are specific to nematodes.
doi:10.1016/j.meegid.2010.07.024
PMCID: PMC3666958  PMID: 20692378
Trichostrongylus colubriformis; Transcriptome; Next-generation sequencing; Bioinformatics; Peptidases; Ancylostoma-secreted proteins
6.  Identification of ovarian cancer associated genes using an integrated approach in a Boolean framework 
BMC Systems Biology  2013;7:12.
Background
Cancer is a complex disease where molecular mechanism remains elusive. A systems approach is needed to integrate diverse biological information for the prognosis and therapy risk assessment using mechanistic approach to understand gene interactions in pathways and networks and functional attributes to unravel the biological behaviour of tumors.
Results
We weighted the functional attributes based on various functional properties observed between cancerous and non-cancerous genes reported from literature. This weighing schema was then encoded in a Boolean logic framework to rank differentially expressed genes. We have identified 17 genes to be differentially expressed from a total of 11,173 genes, where ten genes are reported to be down-regulated via epigenetic inactivation and seven genes are up-regulated. Here, we report that the overexpressed genes IRAK1, CHEK1 and BUB1 may play an important role in ovarian cancer. We also show that these 17 genes can be used to form an ovarian cancer signature, to distinguish normal from ovarian cancer subjects and that the set of three genes, CHEK1, AR, and LYN, can be used to classify good and poor prognostic tumors.
Conclusion
We provided a workflow using a Boolean logic schema for the identification of differentially expressed genes by integrating diverse biological information. This integrated approach resulted in the identification of genes as potential biomarkers in ovarian cancer.
doi:10.1186/1752-0509-7-12
PMCID: PMC3605242  PMID: 23383610
7.  Helminth secretome database (HSD): a collection of helminth excretory/secretory proteins predicted from expressed sequence tags (ESTs) 
BMC Genomics  2012;13(Suppl 7):S8.
Background
Helminths are important socio-economic organisms, responsible for causing major parasitic infections in humans, other animals and plants. These infections impose a significant public health and economic burden globally. Exceptionally, some helminth organisms like Caenorhabditis elegans are free-living in nature and serve as model organisms for studying parasitic infections. Excretory/secretory proteins play an important role in parasitic helminth infections which make these proteins attractive targets for therapeutic use. In the case of helminths, large volume of expressed sequence tags (ESTs) has been generated to understand parasitism at molecular level and for predicting excretory/secretory proteins for developing novel strategies to tackle parasitic infections. However, mostly predicted ES proteins are not available for further analysis and there is no repository available for such predicted ES proteins. Furthermore, predictions have, in the main, focussed on classical secretory pathways while it is well established that helminth parasites also utilise non-classical secretory pathways.
Results
We developed a free Helminth Secretome Database (HSD), which serves as a repository for ES proteins predicted using classical and non-classical secretory pathways, from EST data for 78 helminth species (64 nematodes, 7 trematodes and 7 cestodes) ranging from parasitic to free-living organisms. Approximately 0.9 million ESTs compiled from the largest EST database, dbEST were cleaned, assembled and analysed by different computational tools in our bioinformatics pipeline and predicted ES proteins were submitted to HSD.
Conclusion
We report the large-scale prediction and analysis of classically and non-classically secreted ES proteins from diverse helminth organisms. All the Unigenes (contigs and singletons) and excretory/secretory protein datasets generated from this analysis are freely available. A BLAST server is available at http://estexplorer.biolinfo.org/hsd, for checking the sequence similarity of new protein sequences against predicted helminth ES proteins.
doi:10.1186/1471-2164-13-S7-S8
PMCID: PMC3546426  PMID: 23281827
8.  TranSeqAnnotator: large-scale analysis of transcriptomic data 
BMC Bioinformatics  2012;13(Suppl 17):S24.
Background
The transcriptome of an organism can be studied with the analysis of expressed sequence tag (EST) data sets that offers a rapid and cost effective approach with several new and updated bioinformatics approaches and tools for assembly and annotation. The comprehensive analyses comprehend an organism along with the genome and proteome analysis. With the advent of large-scale sequencing projects and generation of sequence data at protein and cDNA levels, automated analysis pipeline is necessary to store, organize and annotate ESTs.
Results
TranSeqAnnotator is a workflow for large-scale analysis of transcriptomic data with the most appropriate bioinformatics tools for data management and analysis. The pipeline automatically cleans, clusters, assembles and generates consensus sequences, conceptually translates these into possible protein products and assigns putative function based on various DNA and protein similarity searches. Excretory/secretory (ES) proteins inferred from ESTs/short reads are also identified. The TranSeqAnnotator accepts FASTA format raw and quality ESTs along with protein and short read sequences and are analysed with user selected programs. After pre-processing and assembly, the dataset is annotated at the nucleotide, protein and ES protein levels.
Conclusion
TranSeqAnnotator has been developed in a Linux cluster, to perform an exhaustive and reliable analysis and provide detailed annotation. TranSeqAnnotator outputs gene ontologies, protein functional identifications in terms of mapping to protein domains and metabolic pathways. The pipeline is applied to annotate large EST datasets to identify several novel and known genes with therapeutic experimental validations and could serve as potential targets for parasite intervention. TransSeqAnnotator is freely available for the scientific community at http://estexplorer.biolinfo.org/TranSeqAnnotator/.
doi:10.1186/1471-2105-13-S17-S24
PMCID: PMC3521237  PMID: 23282024
9.  An analysis of the transcriptome of Teladorsagia circumcincta: its biological and biotechnological implications 
BMC Genomics  2012;13(Suppl 7):S10.
Background
Teladorsagia circumcincta (order Strongylida) is an economically important parasitic nematode of small ruminants (including sheep and goats) in temperate climatic regions of the world. Improved insights into the molecular biology of this parasite could underpin alternative methods required to control this and related parasites, in order to circumvent major problems associated with anthelmintic resistance. The aims of the present study were to define the transcriptome of the adult stage of T. circumcincta and to infer the main pathways linked to molecules known to be expressed in this nematode. Since sheep develop acquired immunity against T. circumcincta, there is some potential for the development of a vaccine against this parasite. Hence, we infer excretory/secretory molecules for T. circumcincta as possible immunogens and vaccine candidates.
Results
A total of 407,357 ESTs were assembled yielding 39,852 putative gene sequences. Conceptual translation predicted 24,013 proteins, which were then subjected to detailed annotation which included pathway mapping of predicted proteins (including 112 excreted/secreted [ES] and 226 transmembrane peptides), domain analysis and GO annotation was carried out using InterProScan along with BLAST2GO. Further analysis was carried out for secretory signal peptides using SignalP and non-classical sec pathway using SecretomeP tools.
For ES proteins, key pathways, including Fc epsilon RI, T cell receptor, and chemokine signalling as well as leukocyte transendothelial migration were inferred to be linked to immune responses, along with other pathways related to neurodegenerative diseases and infectious diseases, which warrant detailed future studies. KAAS could identify new and updated pathways like phagosome and protein processing in endoplasmic reticulum. Domain analysis for the assembled dataset revealed families of serine, cysteine and proteinase inhibitors which might represent targets for parasite intervention. InterProScan could identify GO terms pertaining to the extracellular region. Some of the important domain families identified included the SCP-like extracellular proteins which belong to the pathogenesis-related proteins (PRPs) superfamily along with C-type lectin, saposin-like proteins. The 'extracellular region' that corresponds to allergen V5/Tpx-1 related, considered important in parasite-host interactions, was also identified.
Six cysteine motif (SXC1) proteins, transthyretin proteins, C-type lectins, activation-associated secreted proteins (ASPs), which could represent potential candidates for developing novel anthelmintics or vaccines were few other important findings. Of these, SXC1, protein kinase domain-containing protein, trypsin family protein, trypsin-like protease family member (TRY-1), putative major allergen and putative lipid binding protein were identified which have not been reported in the published T. circumcincta proteomics analysis.
Detailed analysis of 6,058 raw EST sequences from dbEST revealed 315 putatively secreted proteins. Amongst them, C-type single domain activation associated secreted protein ASP3 precursor, activation-associated secreted proteins (ASP-like protein), cathepsin B-like cysteine protease, cathepsin L cysteine protease, cysteine protease, TransThyretin-Related and Venom-Allergen-like proteins were the key findings.
Conclusions
We have annotated a large dataset ESTs of T. circumcincta and undertaken detailed comparative bioinformatics analyses. The results provide a comprehensive insight into the molecular biology of this parasite and disease manifestation which provides potential focal point for future research. We identified a number of pathways responsible for immune response. This type of large-scale computational scanning could be coupled with proteomic and metabolomic studies of this parasite leading to novel therapeutic intervention and disease control strategies. We have also successfully affirmed the use of bioinformatics tools, for the study of ESTs, which could now serve as a benchmark for the development of new computational EST analysis pipelines.
doi:10.1186/1471-2164-13-S7-S10
PMCID: PMC3521389  PMID: 23282110
10.  The Transcriptome Analysis of Strongyloides stercoralis L3i Larvae Reveals Targets for Intervention in a Neglected Disease 
Background
Strongyloidiasis is one of the most neglected diseases distributed worldwide with endemic areas in developed countries, where chronic infections are life threatening. Despite its impact, very little is known about the molecular biology of the parasite involved and its interplay with its hosts. Next generation sequencing technologies now provide unique opportunities to rapidly address these questions.
Principal Findings
Here we present the first transcriptome of the third larval stage of S. stercoralis using 454 sequencing coupled with semi-automated bioinformatic analyses. 253,266 raw sequence reads were assembled into 11,250 contiguous sequences, most of which were novel. 8037 putative proteins were characterized based on homology, gene ontology and/or biochemical pathways. Comparison of the transcriptome of S. strongyloides with those of other nematodes, including S. ratti, revealed similarities in transcription of molecules inferred to have key roles in parasite-host interactions. Enzymatic proteins, like kinases and proteases, were abundant. 1213 putative excretory/secretory proteins were compiled using a new pipeline which included non-classical secretory proteins. Potential drug targets were also identified.
Conclusions
Overall, the present dataset should provide a solid foundation for future fundamental genomic, proteomic and metabolomic explorations of S. stercoralis, as well as a basis for applied outcomes, such as the development of novel methods of intervention against this neglected parasite.
Author Summary
Strongyloides stercoralis (Nematoda) is an important parasite of humans, causing Strongyloidiasis, considered as one of the most neglected diseases, affecting more than 100 million people worldwide. Chronic infections in endemic areas can be maintained for decades through the autoinfective cycle with the L3 filariform larvae. In these areas, misdiagnosis, inadequate treatment and the facilitation of hyperinfection syndrome by immunosupression are frequent and contribute to a high mortality rate. Among the affected areas, chronic patients have been described in the Valencian Mediterranean coastal region of Spain. Despite its serious impact, very little is known about this parasite and its relationship with its hosts at the molecular level, and more effective diagnostic tests and treatments are needed. Next generation sequencing technologies now provide unique opportunities to rapidly advance in these areas. In this study, we present the first transcriptome of S. stercoralis L3i using 454 sequencing followed by semi-automated bioinformatic analyses. Our study identifies 8037 putative proteins based on homology, gene ontology, and/or biochemical pathways, including putative excretory/secretory proteins as well as potential drug targets. The present dataset provides a useful resource and adds greatly to our understanding of a human parasite affecting both developed and developing countries.
doi:10.1371/journal.pntd.0001513
PMCID: PMC3289599  PMID: 22389732
11.  Towards big data science in the decade ahead from ten years of InCoB and the 1st ISCB-Asia Joint Conference 
BMC Bioinformatics  2011;12(Suppl 13):S1.
The 2011 International Conference on Bioinformatics (InCoB) conference, which is the annual scientific conference of the Asia-Pacific Bioinformatics Network (APBioNet), is hosted by Kuala Lumpur, Malaysia, is co-organized with the first ISCB-Asia conference of the International Society for Computational Biology (ISCB). InCoB and the sequencing of the human genome are both celebrating their tenth anniversaries and InCoB’s goalposts for the next decade, implementing standards in bioinformatics and globally distributed computational networks, will be discussed and adopted at this conference. Of the 49 manuscripts (selected from 104 submissions) accepted to BMC Genomics and BMC Bioinformatics conference supplements, 24 are featured in this issue, covering software tools, genome/proteome analysis, systems biology (networks, pathways, bioimaging) and drug discovery and design.
doi:10.1186/1471-2105-12-S13-S1
PMCID: PMC3278825  PMID: 22372736
12.  In silico approach to screen compounds active against parasitic nematodes of major socio-economic importance 
BMC Bioinformatics  2011;12(Suppl 13):S25.
Background
Infections due to parasitic nematodes are common causes of morbidity and fatality around the world especially in developing nations. At present however, there are only three major classes of drugs for treating human nematode infections. Additionally the scientific knowledge on the mechanism of action and the reason for the resistance to these drugs is poorly understood. Commercial incentives to design drugs that are endemic to developing countries are limited therefore, virtual screening in academic settings can play a vital role is discovering novel drugs useful against neglected diseases. In this study we propose to build robust machine learning model to classify and screen compounds active against parasitic nematodes.
Results
A set of compounds active against parasitic nematodes were collated from various literature sources including PubChem while the inactive set was derived from DrugBank database. The support vector machine (SVM) algorithm was used for model development, and stratified ten-fold cross validation was used to evaluate the performance of each classifier. The best results were obtained using the radial basis function kernel. The SVM method achieved an accuracy of 81.79% on an independent test set. Using the model developed above, we were able to indentify novel compounds with potential anthelmintic activity.
Conclusion
In this study, we successfully present the SVM approach for predicting compounds active against parasitic nematodes which suggests the effectiveness of computational approaches for antiparasitic drug discovery. Although, the accuracy obtained is lower than the previously reported in a similar study but we believe that our model is more robust because we intentionally employed stringent criteria to select inactive dataset thus making it difficult for the model to classify compounds. The method presents an alternative approach to the existing traditional methods and may be useful for predicting hitherto novel anthelmintic compounds.
doi:10.1186/1471-2105-12-S13-S25
PMCID: PMC3278842  PMID: 22373185
13.  InCoB celebrates its tenth anniversary as first joint conference with ISCB-Asia 
BMC Genomics  2011;12(Suppl 3):S1.
In 2009 the International Society for Computational Biology (ISCB) started to roll out regional bioinformatics conferences in Africa, Latin America and Asia. The open and competitive bid for the first meeting in Asia (ISCB-Asia) was awarded to Asia-Pacific Bioinformatics Network (APBioNet) which has been running the International Conference on Bioinformatics (InCoB) in the Asia-Pacific region since 2002. InCoB/ISCB-Asia 2011 is held from November 30 to December 2, 2011 in Kuala Lumpur, Malaysia. Of 104 manuscripts submitted to BMC Genomics and BMC Bioinformatics conference supplements, 49 (47.1%) were accepted. The strong showing of Asia among submissions (82.7%) and acceptances (81.6%) signals the success of this tenth InCoB anniversary meeting, and bodes well for the future of ISCB-Asia.
doi:10.1186/1471-2164-12-S3-S1
PMCID: PMC3333168  PMID: 22369160
14.  In silico secretome analysis approach for next generation sequencing transcriptomic data 
BMC Genomics  2011;12(Suppl 3):S14.
Background
Excretory/secretory proteins (ESPs) play a major role in parasitic infection as they are present at the host-parasite interface and regulate host immune system. In case of parasitic helminths, transcriptomics has been used extensively to understand the molecular basis of parasitism and for developing novel therapeutic strategies against parasitic infections. However, none of transcriptomic studies have extensively covered ES protein prediction for identifying novel therapeutic targets, especially as parasites adopt non-classical secretion pathways.
Results
We developed a semi-automated computational approach for prediction and annotation of ES proteins using transcriptomic data from next generation sequencing platforms. For the prediction of non-classically secreted proteins, we have used an improved computational strategy, together with homology matching to a dataset of experimentally determined parasitic helminth ES proteins. We applied this protocol to analyse 454 short reads of parasitic nematode, Strongyloides ratti. From 296231 reads, we derived 28901 contigs, which were translated into 20877 proteins. Based on our improved ES protein prediction pipeline, we identified 2572 ES proteins, of which 407 (1.9%) proteins have classical N-terminal signal peptides, 923 (4.4%) were computationally identified as non-classically secreted while 1516 (7.26%) were identified by homology to experimentally identified parasitic helminth ES proteins. Out of 2572 ES proteins, 2310 (89.8%) ES proteins had homologues in the free-living nematode Caenorhabditis elegans and 2220 (86.3%) in parasitic nematodes. We could functionally annotate 1591 (61.8%) ES proteins with protein families and domains and establish pathway associations for 691 (26.8%) proteins. In addition, we have identified 19 representative ES proteins, which have no homologues in the host organism but homologous to lethal RNAi phenotypes in C. elegans, as potential therapeutic targets.
Conclusion
We report a comprehensive approach using freely available computational tools for the secretome analysis of NGS data. This approach has been applied to S. ratti 454 transcriptomic data for in silico excretory/secretory proteins prediction and analysis, providing a foundation for developing new therapeutic solutions for parasitic infections.
doi:10.1186/1471-2164-12-S3-S14
PMCID: PMC3333173  PMID: 22369360
15.  A comparative structural bioinformatics analysis of inherited mutations in β-D-Mannosidase across multiple species reveals a genotype-phenotype correlation  
BMC Genomics  2011;12(Suppl 3):S22.
Background
Lysosomal β-D-mannosidase is a glycosyl hydrolase that breaks down the glycosidic bonds at the non-reducing end of N-linked glycoproteins. Hence, it is a crucial enzyme in polysaccharide degradation pathway. Mutations in the MANBA gene that codes for lysosomal β-mannosidase, result in improper coding and malfunctioning of protein, leading to β-mannosidosis. Studying the location of mutations on the enzyme structure is a rational approach in order to understand the functional consequences of these mutations. Accordingly, the pathology and clinical manifestations of the disease could be correlated to the genotypic modifications.
Results
The wild-type and inherited mutations of β-mannosidase were studied across four different species, human, cow, goat and mouse employing a previously demonstrated comprehensive homology modeling and mutational mapping technique, which reveals a correlation between the variation of genotype and the severity of phenotype in β-mannosidosis. X-ray crystallographic structure of β-mannosidase from Bacteroides thetaiotaomicron was used as template for 3D structural modeling of the wild-type enzymes containing all the associated ligands. These wild-type models subsequently served as templates for building mutational structures. Truncations account for approximately 70% of the mutational cases. In general, the proximity of mutations to the active site determines the severity of phenotypic expressions. Mapping mutations to the MANBA gene sequence has identified five mutational hot-spots.
Conclusion
Although restrained by a limited dataset, our comprehensive study suggests a genotype-phenotype correlation in β-mannosidosis. A predictive approach for detecting likely β-mannosidosis is also demonstrated where we have extrapolated observed mutations from one species to homologous positions in other organisms based on the proximity of the mutations to the enzyme active site and their co-location from different organisms. Apart from aiding the detection of mutational hotspots in the gene, where novel mutations could be disease-implicated, this approach also provides a way to predict new disease mutations. Higher expression of the exoglycosidase chitobiase is said to play a vital role in determining disease phenotypes in human and mouse. A bigger dataset of inherited mutations as well as a parallel study of β-mannosidase and chitobiase activities in prospective patients would be interesting to better understand the underlying reasons for β-mannosidosis.
doi:10.1186/1471-2164-12-S3-S22
PMCID: PMC3333182  PMID: 22369051
16.  Understanding TR Binding to pMHC Complexes: How Does a TR Scan Many pMHC Complexes yet Preferentially Bind to One 
PLoS ONE  2011;6(2):e17194.
Understanding the basis of the binding of a T cell receptor (TR) to the peptide-MHC (pMHC) complex is essential due to the vital role it plays in adaptive immune response. We describe the use of computed binding (free) energy (BE), TR paratope, pMHC epitope, molecular surface electrostatic potential (MSEP) and calculated TR docking angle (θ) to analyse 61 TR/pMHC crystallographic structures to comprehend TR/pMHC interaction. In doing so, we have successfully demonstrated a novel/rational approach for θ calculation, obtained a linear correlation between BE and θ without any “codon” or amino acid preference, provided an explanation for TR ability to scan many pMHC ligands yet specifically bind one, proposed a mechanism for pMHC recognition by TR leading to T cell activation and illustrated the importance of the peptide in determining TR specificity, challenging the “germline bias” theory.
doi:10.1371/journal.pone.0017194
PMCID: PMC3043089  PMID: 21364947
17.  Towards BioDBcore: a community-defined information specification for biological databases 
The present article proposes the adoption of a community-defined, uniform, generic description of the core attributes of biological databases, BioDBCore. The goals of these attributes are to provide a general overview of the database landscape, to encourage consistency and interoperability between resources; and to promote the use of semantic and syntactic standards. BioDBCore will make it easier for users to evaluate the scope and relevance of available resources. This new resource will increase the collective impact of the information present in biological databases.
doi:10.1093/database/baq027
PMCID: PMC3017395  PMID: 21205783
18.  Meeting Report from the Second “Minimum Information for Biological and Biomedical Investigations” (MIBBI) workshop 
Standards in Genomic Sciences  2010;3(3):259-266.
This report summarizes the proceedings of the second workshop of the ‘Minimum Information for Biological and Biomedical Investigations’ (MIBBI) consortium held on Dec 1-2, 2010 in Rüdesheim, Germany through the sponsorship of the Beilstein-Institute. MIBBI is an umbrella organization uniting communities developing Minimum Information (MI) checklists to standardize the description of data sets, the workflows by which they were generated and the scientific context for the work. This workshop brought together representatives of more than twenty communities to present the status of their MI checklists and plans for future development. Shared challenges and solutions were identified and the role of MIBBI in MI checklist development was discussed. The meeting featured some thirty presentations, wide-ranging discussions and breakout groups. The top outcomes of the two-day workshop as defined by the participants were: 1) the chance to share best practices and to identify areas of synergy; 2) defining a series of tasks for updating the MIBBI Portal; 3) reemphasizing the need to maintain independent MI checklists for various communities while leveraging common terms and workflow elements contained in multiple checklists; and 4) revision of the concept of the MIBBI Foundry to focus on the creation of a core set of MIBBI modules intended for reuse by individual MI checklist projects while maintaining the integrity of each MI project. Further information about MIBBI and its range of activities can be found at http://mibbi.org/.
doi:10.4056/sigs.147362
PMCID: PMC3035314  PMID: 21304730
19.  Advancing standards for bioinformatics activities: persistence, reproducibility, disambiguation and Minimum Information About a Bioinformatics investigation (MIABi) 
BMC Genomics  2010;11(Suppl 4):S27.
The 2010 International Conference on Bioinformatics, InCoB2010, which is the annual conference of the Asia-Pacific Bioinformatics Network (APBioNet) has agreed to publish conference papers in compliance with the proposed Minimum Information about a Bioinformatics investigation (MIABi), proposed in June 2009. Authors of the conference supplements in BMC Bioinformatics, BMC Genomics and Immunome Research have consented to cooperate in this process, which will include the procedures described herein, where appropriate, to ensure data and software persistence and perpetuity, database and resource re-instantiability and reproducibility of results, author and contributor identity disambiguation and MIABi-compliance. Wherever possible, datasets and databases will be submitted to depositories with standardized terminologies. As standards are evolving, this process is intended as a prelude to the 100 BioDatabases (BioDB100) initiative whereby APBioNet collaborators will contribute exemplar databases to demonstrate the feasibility of standards-compliance and participate in refining the process for peer-review of such publications and validation of scientific claims and standards compliance. This testbed represents another step in advancing standards-based processes in the bioinformatics community which is essential to the growing interoperability of biological data, information, knowledge and computational resources.
doi:10.1186/1471-2164-11-S4-S27
PMCID: PMC3005918  PMID: 21143811
20.  Challenges of the next decade for the Asia Pacific region: 2010 International Conference in Bioinformatics (InCoB 2010) 
BMC Genomics  2010;11(Suppl 4):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.
doi:10.1186/1471-2164-11-S4-S1
PMCID: PMC3005919  PMID: 21143792
21.  Secretome: clues into pathogen infection and clinical applications 
Genome Medicine  2009;1(11):113.
The secretome encompasses the complete set of gene products secreted by a cell. Recent studies on secretome analysis reveal that secretory proteins play an important role in pathogen infection and host-pathogen interactions. Excretory/secretory proteins of pathogens change the host cell environment by suppressing the immune system, to aid the proliferation of infection. Identifying secretory proteins involved in pathogen infection will lead to the discovery of potential drug targets and biomarkers for diagnostic applications.
doi:10.1186/gm113
PMCID: PMC2808748  PMID: 19951402
22.  Towards BioDBcore: a community-defined information specification for biological databases 
Nucleic Acids Research  2010;39(Database issue):D7-D10.
The present article proposes the adoption of a community-defined, uniform, generic description of the core attributes of biological databases, BioDBCore. The goals of these attributes are to provide a general overview of the database landscape, to encourage consistency and interoperability between resources and to promote the use of semantic and syntactic standards. BioDBCore will make it easier for users to evaluate the scope and relevance of available resources. This new resource will increase the collective impact of the information present in biological databases.
doi:10.1093/nar/gkq1173
PMCID: PMC3013734  PMID: 21097465
23.  InCoB2010 - 9th International Conference on Bioinformatics at Tokyo, Japan, September 26-28, 2010 
BMC Bioinformatics  2010;11(Suppl 7):S1.
The International Conference on Bioinformatics (InCoB), the annual conference of the Asia-Pacific Bioinformatics Network (APBioNet), is hosted in one of countries of the Asia-Pacific region. The 2010 conference was awarded to Japan and has attracted more than one hundred high-quality research paper submissions. Thorough peer reviewing resulted in 47 (43.5%) accepted papers out of 108 submissions. Submissions from Japan, R.O. Korea, P.R. China, Australia, Singapore and U.S.A totaled 43.8% and contributed to 57.4% of accepted papers. Manuscripts originating from Taiwan and India added up to 42.8% of submissions and 28.3% of acceptances. The fifteen articles published in this BMC Bioinformatics supplement cover disease informatics, structural bioinformatics and drug design, biological databases and software tools, signaling pathways, gene regulatory and biochemical networks, evolution and sequence analysis.
doi:10.1186/1471-2105-11-S7-S1
PMCID: PMC2957677  PMID: 21106116
24.  Network analysis of human protein location 
BMC Bioinformatics  2010;11(Suppl 7):S9.
Background
Understanding cellular systems requires the knowledge of a protein's subcellular localization (SCL). Although experimental and predicted data for protein SCL are archived in various databases, SCL prediction remains a non-trivial problem in genome annotation. Current SCL prediction tools use amino-acid sequence features and text mining approaches. A comprehensive analysis of protein SCL in human PPI and metabolic networks for various subcellular compartments is necessary for developing a robust SCL prediction methodology.
Results
Based on protein-protein interaction (PPI) and metabolite-linked protein interaction (MLPI) networks of proteins, we have compared, contrasted and analysed the statistical properties across different subcellular compartments. We integrated PPI and metabolic datasets with SCL information of human proteins from LOCATE and GOA (Gene Ontology Annotation) and estimated three statistical properties: Chi-square (χ2) test, Paired Localisation Correlation Profile (PLCP) and network topological measures. For the PPI network, Pearson's chi-square test shows that for the same SCL category, twice as many interacting protein pairs are observed than estimated when compared to non-interacting protein pairs (χ2 = 1270.19, P-value < 2.2 × 10-16), whereas for MLPI, metabolite-linked protein pairs having the same SCL are observed 20% more than expected, compared to non-metabolite linked proteins (χ2 = 110.02, P-value < 2.2 x10-16). To address the issue of proteins with multiple SCLs, we have specifically used the PLCP (Pair Localization Correlation Profile) measure. PLCP analysis revealed that protein interactions are majorly restricted to the same SCL, though significant cross-compartment interactions are seen for nuclear proteins. Metabolite-linked protein pairs are restricted to specific compartments such as the mitochondrion (P-value < 6.0e-07), the lysosome (P-value < 4.7e-05) and the Golgi apparatus (P-value < 1.0e-15). These findings indicate that the metabolic network adds value to the information in the PPI network for the localisation process of proteins in human subcellular compartments.
Conclusions
The MLPI network differs significantly from the PPI network in its SCL distribution. The PPI network shows passive protein interaction, possibly due to its high false positive rate, across different subcellular compartments, which seem to be absent in the MLPI network, as the MLPI network has evolved to maintain high substrate specificity for proteins.
doi:10.1186/1471-2105-11-S7-S9
PMCID: PMC2957692  PMID: 21106131
25.  pDOCK: a new technique for rapid and accurate docking of peptide ligands to Major Histocompatibility Complexes 
Immunome Research  2010;6(Suppl 1):S2.
Background
Identification of antigenic peptide epitopes is an essential prerequisite in T cell-based molecular vaccine design. Computational (sequence-based and structure-based) methods are inexpensive and efficient compared to experimental approaches in screening numerous peptides against their cognate MHC alleles. In structure-based protocols, suited to alleles with limited epitope data, the first step is to identify high-binding peptides using docking techniques, which need improvement in speed and efficiency to be useful in large-scale screening studies. We present pDOCK: a new computational technique for rapid and accurate docking of flexible peptides to MHC receptors and primarily apply it on a non-redundant dataset of 186 pMHC (MHC-I and MHC-II) complexes with X-ray crystal structures.
Results
We have compared our docked structures with experimental crystallographic structures for the immunologically relevant nonameric core of the bound peptide for MHC-I and MHC-II complexes. Primary testing for re-docking of peptides into their respective MHC grooves generated 159 out of 186 peptides with Cα RMSD of less than 1.00 Å, with a mean of 0.56 Å. Amongst the 25 peptides used for single and variant template docking, the Cα RMSD values were below 1.00 Å for 23 peptides. Compared to our earlier docking methodology, pDOCK shows upto 2.5 fold improvement in the accuracy and is ~60% faster. Results of validation against previously published studies represent a seven-fold increase in pDOCK accuracy.
Conclusions
The limitations of our previous methodology have been addressed in the new docking protocol making it a rapid and accurate method to evaluate pMHC binding. pDOCK is a generic method and although benchmarks against experimental structures, it can be applied to alleles with no structural data using sequence information. Our outcomes establish the efficacy of our procedure to predict highly accurate peptide structures permitting conformational sampling of the peptide in MHC binding groove. Our results also support the applicability of pDOCK for in silico identification of promiscuous peptide epitopes that are relevant to higher proportions of human population with greater propensity to activate T cells making them key targets for the design of vaccines and immunotherapies.
doi:10.1186/1745-7580-6-S1-S2
PMCID: PMC2946780  PMID: 20875153

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