S3DB core: a framework for RDF generation and management in bioinformatics infrastructures

Background  

Biomedical research is set to greatly benefit from the use of semantic web technologies in the design of computational infrastructure. However, beyond well defined research initiatives, substantial issues of data heterogeneity, source distribution, and privacy currently stand in the way towards the personalization of Medicine.     

XMPP for cloud computing in bioinformatics supporting discovery and invocation of asynchronous web services

Background  

Life sciences make heavily use of the web for both data provision and analysis. However, the increasing amount of available data and the diversity of analysis tools call for machine accessible interfaces in order to be effective. HTTP-based Web service technologies, like the Simple Object Access Protocol (SOAP) and REpresentational State Transfer (REST) services, are today the most common technologies for this in bioinformatics. However, these methods have severe drawbacks, including lack of discoverability, and the inability for services to send status notifications. Several complementary workarounds have been proposed, but the results are ad-hoc solutions of varying quality that can be difficult to use.     

dictyExpress: a Dictyostelium discoideum gene expression database with an explorative data analysis web-based interface

Background  

Bioinformatics often leverages on recent advancements in computer science to support biologists in their scientific discovery process. Such efforts include the development of easy-to-use web interfaces to biomedical databases. Recent advancements in interactive web technologies require us to rethink the standard submit-and-wait paradigm, and craft bioinformatics web applications that share analytical and interactive power with their desktop relatives, while retaining simplicity and availability.     

A web services choreography scenario for interoperating bioinformatics applications

Background  

Very often genome-wide data analysis requires the interoperation of multiple databases and analytic tools. A large number of genome databases and bioinformatics applications are available through the web, but it is difficult to automate interoperation because: 1) the platforms on which the applications run are heterogeneous, 2) their web interface is not machine-friendly, 3) they use a non-standard format for data input and output, 4) they do not exploit standards to define application interface and message exchange, and 5) existing protocols for remote messaging are often not firewall-friendly. To overcome these issues, web services have emerged as a standard XML-based model for message exchange between heterogeneous applications. Web services engines have been developed to manage the configuration and execution of a web services workflow.     

INTEGRATOR: interactive graphical search of large protein interactomes over the Web

Background  

The rapid growth of protein interactome data has elevated the necessity and importance of network analysis tools. However, unlike pure text data, network search spaces are of exponential complexity. This poses special challenges for storing, searching, and navigating this data efficiently. Moreover, development of effective web interfaces has been difficult.     

CaGrid Workflow Toolkit: A taverna based workflow tool for cancer grid

Background  

In biological and medical domain, the use of web services made the data and computation functionality accessible in a unified manner, which helped automate the data pipeline that was previously performed manually. Workflow technology is widely used in the orchestration of multiple services to facilitate in-silico research. Cancer Biomedical Informatics Grid (caBIG) is an information network enabling the sharing of cancer research related resources and caGrid is its underlying service-based computation infrastructure. CaBIG requires that services are composed and orchestrated in a given sequence to realize data pipelines, which are often called scientific workflows.     

Identification of similar regions of protein structures using integrated sequence and structure analysis tools

Background  

Understanding protein function from its structure is a challenging problem. Sequence based approaches for finding homology have broad use for annotation of both structure and function. 3D structural information of protein domains and their interactions provide a complementary view to structure function relationships to sequence information. We have developed a web site and an API of web services that enables users to submit protein structures and identify statistically significant neighbors and the underlying structural environments that make that match using a suite of sequence and structure analysis tools. To do this, we have integrated S-BLEST, PSI-BLAST and HMMer based superfamily predictions to give a unique integrated view to prediction of SCOP superfamilies, EC number, and GO term, as well as identification of the protein structural environments that are associated with that prediction. Additionally, we have extended UCSF Chimera and PyMOL to support our web services, so that users can characterize their own proteins of interest.     

Metabolite coupling in genome-scale metabolic networks

Background  

Biochemically detailed stoichiometric matrices have now been reconstructed for various bacteria, yeast, and for the human cardiac mitochondrion based on genomic and proteomic data. These networks have been manually curated based on legacy data and elementally and charge balanced. Comparative analysis of these well curated networks is now possible. Pairs of metabolites often appear together in several network reactions, linking them topologically. This co-occurrence of pairs of metabolites in metabolic reactions is termed herein "metabolite coupling." These metabolite pairs can be directly computed from the stoichiometric matrix, S. Metabolite coupling is derived from the matrix ŜŜ ^T, whose off-diagonal elements indicate the number of reactions in which any two metabolites participate together, where Ŝ is the binary form of S.     

Barriers to uptake of services for coronary heart disease: qualitative study

ObjectivesTo identify factors within the South Yorkshire coalfields that influence use of health services by people with angina.DesignQualitative study using semistructured individual and group interviews.SettingGeneral practice and community settings in Barnsley and Rotherham health authorities.Participants14 patients with stable angina and nine primary care staff had individual interviews plus five community groups and one group of general practitioners.ResultsA complex web of factors was identified that prevented, delayed, or facilitated referral to secondary care. Delay, denial, and self management by patients meant that the full extent of symptoms often remained hidden from general practitioners, resulting in a delayed or missed referral. Barriers identified fell into six categories: structural, personal, social and cultural, past experience and expectations, diagnostic confusion, and knowledge and awareness.ConclusionsMany of the factors influencing referral operate before general practitioners become involved. Community development could be one way of tackling inequalities and promoting sustainable change. Structural changes are needed to improve access and increase the acceptability of general practice services. Primary care staff should be educated to detect underreporting of symptoms and promote appropriate referral.

What is already known on this topic

An inverse correlation has been shown between deprivation and cardiac revascularisationFear of hospitals, denial of ill health, and low expectations may prevent people with angina accessing health services

What this study adds

Fear, denial, and low expectations were important barriers to accessing health services, reinforcing earlier findingsOther factors may be specific to the study population—for example, coping, independence, and attributing symptoms to industrially related lung diseaseMany of the barriers operate before general practitioners are involved, making it difficult to identify solutions     

Network-level analysis of metabolic regulation in the human red blood cell using random sampling and singular value decomposition

Background  

Extreme pathways (ExPas) have been shown to be valuable for studying the functions and capabilities of metabolic networks through characterization of the null space of the stoichiometric matrix (S). Singular value decomposition (SVD) of the ExPa matrix P has previously been used to characterize the metabolic regulatory problem in the human red blood cell (hRBC) from a network perspective. The calculation of ExPas is NP-hard, and for genome-scale networks the computation of ExPas has proven to be infeasible. Therefore an alternative approach is needed to reveal regulatory properties of steady state solution spaces of genome-scale stoichiometric matrices.     

Assessment of allelic diversity in intron-containing Mal d 1 genes and their association to apple allergenicity

Background  

Mal d 1 is a major apple allergen causing food allergic symptoms of the oral allergy syndrome (OAS) in birch-pollen sensitised patients. The Mal d 1 gene family is known to have at least 7 intron-containing and 11 intronless members that have been mapped in clusters on three linkage groups. In this study, the allelic diversity of the seven intron-containing Mal d 1 genes was assessed among a set of apple cultivars by sequencing or indirectly through pedigree genotyping. Protein variant constitutions were subsequently compared with Skin Prick Test (SPT) responses to study the association of deduced protein variants with allergenicity in a set of 14 cultivars.     

Finding gene regulatory network candidates using the gene expression knowledge base

Background

Network-based approaches for the analysis of large-scale genomics data have become well established. Biological networks provide a knowledge scaffold against which the patterns and dynamics of ‘omics’ data can be interpreted. The background information required for the construction of such networks is often dispersed across a multitude of knowledge bases in a variety of formats. The seamless integration of this information is one of the main challenges in bioinformatics. The Semantic Web offers powerful technologies for the assembly of integrated knowledge bases that are computationally comprehensible, thereby providing a potentially powerful resource for constructing biological networks and network-based analysis.

Results

We have developed the Gene eXpression Knowledge Base (GeXKB), a semantic web technology based resource that contains integrated knowledge about gene expression regulation. To affirm the utility of GeXKB we demonstrate how this resource can be exploited for the identification of candidate regulatory network proteins. We present four use cases that were designed from a biological perspective in order to find candidate members relevant for the gastrin hormone signaling network model. We show how a combination of specific query definitions and additional selection criteria derived from gene expression data and prior knowledge concerning candidate proteins can be used to retrieve a set of proteins that constitute valid candidates for regulatory network extensions.

Conclusions

Semantic web technologies provide the means for processing and integrating various heterogeneous information sources. The GeXKB offers biologists such an integrated knowledge resource, allowing them to address complex biological questions pertaining to gene expression. This work illustrates how GeXKB can be used in combination with gene expression results and literature information to identify new potential candidates that may be considered for extending a gene regulatory network.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-014-0386-y) contains supplementary material, which is available to authorized users.     

Allele distribution and genetic diversity of VNTR loci in <Emphasis Type="Italic">Salmonella enterica</Emphasis>serotype Enteritidis isolates from different sources

Background  

Salmonella enterica serotype Enteritidis (S. Enteritidis) is a zoonotic pathogen, which can be found in many sources including animals and the environment. However, little is known about the molecular relatedness among S. Enteritidis isolates from different sources. We have applied multiple-locus variable number tandem repeat analysis (MLVA) to study the genetic diversity of S. Enteritidis isolates from human and non-human sources.     

Biotransformation of β-keto nitriles to chiral (<Emphasis Type="Italic">S</Emphasis>)-β-amino acids using nitrilase and ω-transaminase

Objective

To enzymatically synthesize enantiomerically pure β-amino acids from β-keto nitriles using nitrilase and ω-transaminase.

Results

An enzyme cascade system was designed where in β-keto nitriles are initially hydrolyzed to β-keto acids using nitrilase from Bradyrhizobium japonicum and subsequently β-keto acids were converted to β-amino acids using ω-transaminases. Five different ω-transaminases were tested for this cascade reaction, To enhance the yields of β-amino acids, the concentrations of nitrilase and amino donor were optimized. Using this enzymatic reaction, enantiomerically pure (S)-β-amino acids (ee > 99%) were generated. As nitrilase is the bottleneck in this reaction, molecular docking analysis was carried out to depict the poor affinity of nitrilase towards β-keto acids.

Conclusions

A novel enzymatic route to generate enantiomerically pure aromatic (S)-β-amino acids from β-keto nitriles is demonstrated for the first time.

     

Accessing the SEED Genome Databases via Web Services API: Tools for Programmers

Background  

The SEED integrates many publicly available genome sequences into a single resource. The database contains accurate and up-to-date annotations based on the subsystems concept that leverages clustering between genomes and other clues to accurately and efficiently annotate microbial genomes. The backend is used as the foundation for many genome annotation tools, such as the Rapid Annotation using Subsystems Technology (RAST) server for whole genome annotation, the metagenomics RAST server for random community genome annotations, and the annotation clearinghouse for exchanging annotations from different resources. In addition to a web user interface, the SEED also provides Web services based API for programmatic access to the data in the SEED, allowing the development of third-party tools and mash-ups.     

Natural history of <Emphasis Type="Italic">S</Emphasis>-adenosylmethionine-binding proteins

Background  

S-adenosylmethionine is a source of diverse chemical groups used in biosynthesis and modification of virtually every class of biomolecules. The most notable reaction requiring S-adenosylmethionine, transfer of methyl group, is performed by a large class of enzymes, S-adenosylmethionine-dependent methyltransferases, which have been the focus of considerable structure-function studies. Evolutionary trajectories of these enzymes, and especially of other classes of S-adenosylmethionine-binding proteins, nevertheless, remain poorly understood. We addressed this issue by computational comparison of sequences and structures of various S-adenosylmethionine-binding proteins.     

Direct and indirect transmission of four <Emphasis Type="Italic">Salmonella enterica</Emphasis> serotypes in pigs

Background  

Feed-borne spread of Salmonella spp. to pigs has been documented several times in recent years in Sweden. Experiences from the field suggest that feed-associated serotypes might be less transmittable and subsequently easier to eradicate from pig herds than other serotypes more commonly associated to pigs. Four Salmonella serotypes were selected for experimental studies in pigs in order to study transmissibility and compare possible differences between feed-assoociated (S Cubana and S Yoruba) and pig-associated serotypes (S Derby and S Typhimurium).