bluuebunny/crossref_metadata_2025_split huggingface dataset:
Prediction of transcription factor binding to DNA using rule induction methods
Authors: Huss Mikael , Nordström Karin 
Published: December 2017

Abstract In this study, we seek to develop a predictive model for finding the strength of binding between a particular transcription factor (TF) variant and a particular DNA target variant. The DNA binding paired domains of the Pax transcription factors, which are our main focus, show seemingly fuzzy and degenerate binding to various DNA targets, and paired domain-DNA binding is not a problem well suited for previously proposed algorithms. Here, we introduce a simple way to use rule induction for predicting the strength of TFDNA binding. We have created a dataset consisting of 597 example cases for paired domain-DNA binding by collecting information about all published and quantified interactions between TF and DNA sequence variants. Application of the rule induction based method on this dataset yields a high, although far from ideal accuracy of 69.7% (based on cross-validation), but perhaps more importantly, several useful rules for predicting the binding strength have been found. Although the primary motivation for introducing the rule induction based methods is the lack of efficient algorithms for paired domain-DNA binding prediction, we also show that the method can be applied with some success to a more well-studied TF-DNA binding prediction task involving the early growth response (EGR) TF family.
The GeWare data warehouse platform for the analysis of molecular-biological and clinical data
Authors: Rahm Erhard , Kirsten Toralf , Lange Jörg 
Published: December 2017

Abstract We introduce the GeWare data warehouse platform for the integrated analysis of clinical information, microarray data and annotations within large biomedical research studies. Clinical data is obtained from a commercial study management system while publicly available data is integrated using a mediator approach. The platform utilizes a generic approach to manage different types of annotations. We outline the overall architecture of the platform, its implementation as well as the main processing and analysis workflows.
From MIN model to ordinary differential equations
Authors: Yartseva A. , Devillers R. , Klaudel H. , Képès F. 
Published: December 2017

Summary Biological interaction networks can be modeled using the Modular Interaction Network (MIN) formalism, which provides an intermediary modeling level between the biological and mathematical ones. MIN focuses on a simple but structured and versatile representation of biological knowledge, without targeting a particular analysis or simulation technique. In this paper, we propose a translation procedure which, starting from a MIN specification of a biological system, generates its representation in ordinary differential equations (ODEs) allowing to study the dynamics of the system. The translation is illustrated on a classical benchmark: the λ phage genetic switch.
The OXL format for the exchange of integrated datasets
Authors: Taubert Jan , Sieren Klaus Peter , Hindle Matthew , Hoekman Berend , Winnenburg Rainer , Philippi Stephan , Rawlings Chris , Köhler Jacob 
Published: December 2017

Abstract A prerequisite for systems biology is the integration and analysis of heterogeneous experimental data stored in hundreds of life-science databases and millions of scientific publications. Several standardised formats for the exchange of specific kinds of biological information exist. Such exchange languages facilitate the integration process; however they are not designed to transport integrated datasets. A format for exchanging integrated datasets needs to i) cover data from a broad range of application domains, ii) be flexible and extensible to combine many different complex data structures, iii) include metadata and semantic definitions, iv) include inferred information, v) identify the original data source for integrated entities and vi) transport large integrated datasets. Unfortunately, none of the exchange formats from the biological domain (e.g. BioPAX, MAGE-ML, PSI-MI, SBML) or the generic approaches (RDF, OWL) fulfil these requirements in a systematic way.We present OXL, a format for the exchange of integrated data sets, and detail how the aforementioned requirements are met within the OXL format. OXL is the native format within the data integration and text mining system ONDEX. Although OXL was developed with the ONDEX system in mind, it also has the potential to be used in several other biological and non-biological applications described in this paper.Availability: The OXL format is an integral part of the ONDEX system which is freely available under the GPL at http://ondex.sourceforge.net/. Sample files can be found at http://prdownloads.sourceforge.net/ondex/ and the XML Schema at http://ondex.svn.sf.net/viewvc/*checkout*/ondex/trunk/backend/data/xml/ondex.xsd.
VINEdb: a data warehouse for integration and interactive exploration of life science data
Authors: Hariharaputran Sridhar , Töpel Thoralf , Brockschmidt Björn , Hofestädt Ralf 
Published: December 2017

Abstract Control of cell proliferation, differentiation, activation and cell removal is crucial for the development and existence of multi-cellular organisms. Apoptosis, or programmed cell death, is a major control mechanism by which cells die and is also important in controlling cell number and proliferation as part of normal development. Molecular networks that regulate these processes are critical targets for drug development, gene therapy, and metabolic engineering. The molecular interactions involved in this and other processes are analyzed and annotated by experts and stored as data in different databases. The key task is to integrate, manage and visualize these data available from different sources and present them in a user-comprehensible manner.Here we present VINEdb, a data warehouse developed to interact with and to explore integrated life science data. Extendable open source data warehouse architecture enables platform-independent usability of the web application and the underlying infrastructure. A high degree of transparency and up-to-dateness is ensured by a monitor component to control and update the data from the sources. Furthermore, the system is supported by a visualization component to allow interactive graphical exploration of the integrated data. We will use apoptotic pathway and caspase-3 as a case study to show capability and usability of our approach. VINEdb is available at http://tunicata.techfak.unibielefeld.de/VINEdb/.
Developmental Anatomy Ontology of Zebrafish: an Integrative semantic framework
Authors: Belmamoune Mounia , Verbeek Fons J. 
Published: December 2017

Summary Integration of information is quintessential to make use of the wealth of bioinformatics resources. One aspect of integration is to make databases interoperable through well annotated information. With new databases one strives to store complementary information and such results in collections of heterogeneous information systems. Concepts in these databases need to be connected and ontologies typically provide a common terminology to share information among different resources.Our focus of research is the zebrafish and we have developed several information systems in which ontologies are crucial. Pivot is an ontology describing the developmental anatomy, referred to as the Developmental Anatomy Ontolgoy of Zebrafish (DAOZ). The anatomical and temporal concepts are provided by the Zebrafish Information Network (ZFIN) and proven within the research community. We have constructed a 3D digital atlas of zebrafish development based on histology; the atlas is series of volumetric models; in each instance, every volume element is assigned to an anatomical term. Complementing the atlas we developed an information system with 3D patterns of gene expression in zebrafish development based on marker genes. The spatial and temporal annotations to these 3D images are drawn from the ontology that we have designed. In its design the DAOZ ontology is structured as a Directed Acyclic Graph (DAG). Such is required to find unique concept paths and prevent self referencing.As we need to address the ontology in a direct manner, the DAG structure is transferred to a database. The database is used in the integration of our databases that share concepts at different levels of aggregation. In order to make sure that sufficient levels of aggregation for applications in mind are present, the original vocabulary was enriched with more relations and concepts. Both databases can now be addressed with the same unique terms and co-occurrence and co-expression of genes can be readily extracted from the databases. Integration can be further extended to the ZFIN resource and also by including ontologies that relate to gene/gene expression (e.g. Gene Ontology). In this manner, interoperable information retrieval from heterogeneous databases can be realized. This greatly facilitates processing complex information and retrieving relations in the data through machine learning approaches.
Monophyletic clustering and characterization of protein families
Authors: Zhang Jian , Zhao Zhiyuan , Evershed Jennifer , Li Guoying 
Published: December 2017

Summary A protein family contains sequences that are evolutionarily related. Generally, this is reflected by sequence similarity. There have been many attempts to organize the set of protein families into evolutionarily homogenous clusters using certain clustering methods. How do we characterize these clusters? How can we cluster protein families using these characterizations? In this work, these questions were addressed by use of a concept called group-wide co-evolution, and was exemplified by some real and simulated protein family data. The results have shown that the trend of a group of monophyletic proteins might be characterized by a normal distribution, while the strength and variability of this trend can be described by the sample mean and variance of the observed correlation coefficients after a suitable transformation. To exploit this property, we have developed a monophyletic clustering method called monophyletic k−medoids clustering. A software package written in R has been made available at http://www.kent.ac.uk/ims/personal/jz .
A Methodology for Comparative Functional Genomics
Authors: Alam Intikhab , Cornell Mike , Soanes Darren M. , Hedeler Cornelia , Wong Han Min , Rattray Magnus , Hubbard Simon J. , Talbot Nicholas J. , Oliver Stephen G. , Paton Norman W. 
Published: December 2017

Abstract The continuing and rapid increase in the number of fully sequenced genomes is creating new opportunities for comparative studies. However, although many genomic databases store data from multiple organisms, for the most part they provide limited support for comparative genomics. We argue that refocusing genomic data management to provide more direct support for comparative studies enables systematic identification of important relationships between species, thereby increasing the value that can be obtained from sequenced genomes. The principal result of the paper is a methodology, in which comparative analyses are constructed over a foundation based on sequence clusters and evolutionary relationships. This methodology has been applied in a systematic study of the fungi, and we describe how comparative analyses have been implemented as an analysis library over the e-Fungi data warehouse.
Functional and Transcriptional Coherency of Modules in the Human Protein Interaction Network
Authors: Futschik Matthias E. , Chaurasia Gautam , Tschaut Anna , Russ Jenny , Babu M. Madan , Herzel Hanspeter 
Published: December 2017

Summary Modularity is a major design principle in interaction networks. Various studies have shown that protein interaction networks in prokaryotes and eukaryotes display a modular structure. A majority of the studies have been performed for the yeast interaction network, for which data have become abundant. The systematic examination of the human protein interaction network, however, is still in an early phase. To assess whether the human interaction network similarly displays a modular structure, we assembled a large protein network consisting of over 30,000 interactions. More than 670 modules were subsequently identified based on the detection of cliques. Inspection showed that these modules included numerous known protein complexes. The extracted modules were scrutinized for their coherency with respect to function, localization and expression, thereby allowing us to distinguish between stable and dynamic modules. Finally, the examination of the overlap between modules identified key proteins linking distinct molecular processes.
CIDA: An integrated software for the design, characterisation and global comparison of microarrays
Authors: Khalid Sabah , Khan Mohsin , Symonds Alistair , Fraser Karl , Wang Ping , Liu Xiaohui , Li Suling 
Published: December 2017

Abstract Microarray technology has had a significant impact in the field of systems biology involving the investigation into the biological systems that regulate human life. Identifying genes of significant interest within any given disease on an individual basis is no doubt time consuming and inefficient when considering the complexity of the human genome. Thus, the genetic profiling of the entire human genome in a single experiment has resulted in microarray technology becoming a widely used experimental tool. However, without the use of tools for several aspects of microarray data analysis the technology is limited. To date, no such tool has been developed that allows the integration of numerous microarray results from different research laboratories as well as the design of customised gene chips in a cost-effective manner. In light of this, we have designed the first integrated and automated software called Chip Integration, Design and Annotation (CIDA) for the cross comparison, design and functional annotation of microarray gene chips. The software provides molecular biologists with the control to cross compare the biological signatures generated from multiple microarray studies, design custom microarray gene chips based on their research requirements and lastly characterise microarray data in the context of immunogenomics. Through the relative comparison of related microarray experiments we have identified 258 genes with common gene expression profiles that are not only upregulated in anergic T cells, but also in cells over-expressing the transcription factor Egr2, that has been identified to play a role in T cell anergy. Using the gene chip design aspect of CIDA we have designed and subsequently fabricate immuno-tolerance gene chips consisting of 1758 genes for further research.The software and database schema is freely available at ftp://ftp.brunel.ac.uk/cspgssk/CIDA/. Additional material is available online at http://www.brunel.ac.uk/about/acad/health/healthres/researchgroups/mi/publications/supplementary/cida
Mapping protein information to disease terminologies
Authors: Mottaz Anaïs , Yip Yum L. , Ruch Patrick , Veuthey Anne-Lise 
Published: December 2017

Abstract In order to improve the accessibility of genomic and proteomic information to medical researchers, we have developed a procedure to link biological information on proteins involved in diseases to the MeSH and ICD-10 disease terminologies. For this purpose, we took advantage of the manually curated disease annotations in more than 2,000 human protein entries of the UniProt KnowledgeBase. We mapped disease names extracted from the entry comment lines or from the corresponding OMIM entry to the MeSH. The method was assessed on a benchmark set of 200 manually mapped disease comment lines. We obtained a recall of 54% for 91% precision. The same procedure was used to map the more than 3,000 diseases in Swiss-Prot to MeSH with comparable efficiency. Tested on ICD-10, the coverage of the mapped terms was lower, which could be explained by the coarse-grained structure of this terminology for hereditary disease description. The mapping is provided as supplementary material at http://research.isbsib.ch/unimed.
Reactome: An integrated expert model of human molecular processes and access toolkit
Authors: Bono Bernard de , Vastrik Imre , D’Eustachio Peter , Schmidt Esther , Gopinath Gopal , Croft David , Gillespie Marc , Jassal Bijay , Lewis Suzanna , Matthews Lisa , Wu Guanming , Birney Ewan , Stein Lincoln 
Published: December 2017

Summary The behaviour of pervasive molecular processes in human biology can be studied through the large-scale modeling of the molecular events that define them. Constructing detailed models of such extent and scope is a considerable undertaking well beyond the reach and capability of individual efforts, due to the range of expertise required. Reactome (http://www.reactome.org) is an open-access project that collaborates with field experts to integrate their pathway knowledge into a single quality-checked human model. This resource dataset is systematically cross-referenced to major molecular and literature databases, and is accessible to the community in a number of well-established formats. Various tools have been developed to facilitate querying and interaction with this content. The salient features of the annotation strategy are discussed here, and examples of pathway and genomic data integration using flexible interfacing methods from the associated toolkit are also presented.
Integrative Visual Analysis of the Effects of Alternative Splicing on Protein Domain Interaction Networks
Authors: Emig Dorothea , Cline Melissa S. , Klein Karsten , Kunert Anne , Mutzel Petra , Lengauer Thomas , Albrecht Mario 
Published: December 2017

SummaryProteins and their interactions are essential for the functioning of all organisms and for understanding biological processes. Alternative splicing is an important molecular mechanism for increasing the protein diversity in eukaryotic cells. Splicing events that alter the protein structure and the domain composition can be responsible for the regulation of protein interactions and the functional diversity of different tissues. Discovering the occurrence of splicing events and studying protein isoforms have become feasible using Affymetrix Exon Arrays. Therefore, we have developed the versatile Cytoscape plugin DomainGraph that allows for the visual analysis of protein domain interaction networks and their integration with exon expression data. Protein domains affected by alternative splicing are highlighted and splicing patterns can be compared.
Discovering Distinct Patterns in Gene Expression Profiles
Authors: Teng Li , Chan Laiwan 
Published: December 2017

SummaryTraditional analysis of gene expression profiles use clustering to find groups of coexpressed genes which have similar expression patterns. However clustering is time consuming and could be diffcult for very large scale dataset. We proposed the idea of Discovering Distinct Patterns (DDP) in gene expression profiles. Since patterns showing by the gene expressions reveal their regulate mechanisms. It is significant to find all different patterns existing in the dataset when there is little prior knowledge. It is also a helpful start before taking on further analysis. We propose an algorithm for DDP by iteratively picking out pairs of gene expression patterns which have the largest dissimilarities. This method can also be used as preprocessing to initialize centers for clustering methods, like K-means. Experiments on both synthetic dataset and real gene expression datasets show our method is very effective in finding distinct patterns which have gene functional significance and is also effcient.
Conservation of the LexA repressor binding site in Deinococcus radiodurans
Authors: Khan Feroz , Singh S. P. , Mishra B. N. 
Published: December 2017

Summary The LexA protein is a transcriptional repressor of the bacterial SOS DNA repair system, which comprises a set of DNA repair and cellular survival genes that are induced in response to DNA damage. Its varied DNA binding motifs have been characterized and reported in the Escherichia coli, Bacillus subtilis, rhizobia family members, marine magnetotactic bacterium, Salmonella typhimurium and recently in Mycobacterium tuberculosis and this motifs information has been used in our theoretical analysis to detect its novel regulated genes in radio-resistant Deinococcus radiodurans genome. This bacterium showed presence of SOS-box like consensus sequence in the upstream sequences of 3166 genes with >60% motif score similarity percentage (MSSP) on both strands. Attempts to identify LexA-binding sites and the composition of the putative SOS regulon in D. radiodurans have been unsuccessful so far. To resolve the problem we performed theoretical analysis with modifications on reported data set of genes related to DNA repair (61 genes), stress response (145 genes) and some unusual predicted operons (21 clusters). Expression of some of the predicted SOS-box regulated operon members then was examined through the previously reported microarray data which confirm the expression of only single predicted operon i.e. DRB0143 (AAA superfamily NTPase related to 5-methylcytosine specific restriction enzyme subunit McrB) and DRB0144 (homolog of the McrC subunit of the McrBC restriction modification system). The methodology involved weight matrix construction through CONSENSUS algorithm using information of conserved upstream sequences of eight known genes including dinB, tagC, lexA, recA, uvrB, yneA of B. subtilis while lexA and recA of D. radiodurans through phylogenetic footprinting method and later detection of similar conserved SOS-box like LexA binding motifs through both RSAT & PoSSuMsearch programs. The resultant DNA consensus sequence had highly conserved 14 bp SOS-box like binding site.
WebStruct and VisualStruct: web interfaces and visualization for Structure software implemented in a cluster environment
Authors: Jayashree B. , Rajgopal S. , Hoisington D. , Prasanth V.P. , Chandra S. 
Published: December 2017

AbstractStructure, is a widely used software tool to investigate population genetic structure with multi-locus genotyping data. The software uses an iterative algorithm to group individuals into “K” clusters, representing possibly K genetically distinct subpopulations. The serial implementation of this programme is processor-intensive even with small datasets. We describe an implementation of the program within a parallel framework. Speedup was achieved by running different replicates and values of K on each node of the cluster. A web-based user-oriented GUI has been implemented in PHP, through which the user can specify input parameters for the programme. The number of processors to be used can be specified in the background command. A web-based visualization tool “Visualstruct”, written in PHP (HTML and Java script embedded), allows for the graphical display of population clusters output from Structure, where each individual may be visualized as a line segment with K colors defining its possible genomic composition with respect to the K genetic sub-populations. The advantage over available programs is in the increased number of individuals that can be visualized. The analyses of real datasets indicate a speedup of up to four, when comparing the speed of execution on clusters of eight processors with the speed of execution on one desktop. The software package is freely available to interested users upon request.