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1.  A tale of two drug targets: the evolutionary history of BACE1 and BACE2 
Frontiers in Genetics  2013;4:293.
The beta amyloid (APP) cleaving enzyme (BACE1) has been a drug target for Alzheimer's Disease (AD) since 1999 with lead inhibitors now entering clinical trials. In 2011, the paralog, BACE2, became a new target for type II diabetes (T2DM) having been identified as a TMEM27 secretase regulating pancreatic β cell function. However, the normal roles of both enzymes are unclear. This study outlines their evolutionary history and new opportunities for functional genomics. We identified 30 homologs (UrBACEs) in basal phyla including Placozoans, Cnidarians, Choanoflagellates, Porifera, Echinoderms, Annelids, Mollusks and Ascidians (but not Ecdysozoans). UrBACEs are predominantly single copy, show 35–45% protein sequence identity with mammalian BACE1, are ~100 residues longer than cathepsin paralogs with an aspartyl protease domain flanked by a signal peptide and a C-terminal transmembrane domain. While multiple paralogs in Trichoplax and Monosiga pre-date the nervous system, duplication of the UrBACE in fish gave rise to BACE1 and BACE2 in the vertebrate lineage. The latter evolved more rapidly as the former maintained the emergent neuronal role. In mammals, Ka/Ks for BACE2 is higher than BACE1 but low ratios for both suggest purifying selection. The 5' exons show higher Ka/Ks than the catalytic section. Model organism genomes show the absence of certain BACE human substrates when the UrBACE is present. Experiments could thus reveal undiscovered substrates and roles. The human protease double-target status means that evolutionary trajectories and functional shifts associated with different substrates will have implications for the development of clinical candidates for both AD and T2DM. A rational basis for inhibition specificity ratios and assessing target-related side effects will be facilitated by a more complete picture of BACE1 and BACE2 functions informed by their evolutionary context.
doi:10.3389/fgene.2013.00293
PMCID: PMC3865767  PMID: 24381583
BACE1; BACE2; Alzheimer's Disease; type II diabetes; protein family evolution
2.  Editorial: biological ontologies and semantic biology 
doi:10.3389/fgene.2014.00018
PMCID: PMC3912459  PMID: 24550936
semantic biology; biological ontologies; semantic web; data representation; data analysis
3.  Functional modelling of planar cell polarity: an approach for identifying molecular function 
Background
Cells in some tissues acquire a polarisation in the plane of the tissue in addition to apical-basal polarity. This polarisation is commonly known as planar cell polarity and has been found to be important in developmental processes, as planar polarity is required to define the in-plane tissue coordinate system at the cellular level.
Results
We have built an in-silico functional model of cellular polarisation that includes cellular asymmetry, cell-cell signalling and a response to a global cue. The model has been validated and parameterised against domineering non-autonomous wing hair phenotypes in Drosophila.
Conclusions
We have carried out a systematic comparison of in-silico polarity phenotypes with patterns observed in vivo under different genetic manipulations in the wing. This has allowed us to classify the specific functional roles of proteins involved in generating cell polarity, providing new hypotheses about their specific functions, in particular for Pk and Dsh. The predictions from the model allow direct assignment of functional roles of genes from genetic mosaic analysis of Drosophila wings.
doi:10.1186/1471-213X-13-20
PMCID: PMC3662592  PMID: 23672397
Planar polarity; PCP; Mathematical modelling; Self organisation; Drosophila; In-silico phenotyping
4.  NucleoFinder: a statistical approach for the detection of nucleosome positions 
Bioinformatics  2013;29(6):711-716.
Motivation: The identification of nucleosomes along the chromatin is key to understanding their role in the regulation of gene expression and other DNA-related processes. However, current experimental methods (MNase-ChIP, MNase-Seq) sample nucleosome positions from a cell population and contain biases, making thus the precise identification of individual nucleosomes not straightforward. Recent works have only focused on the first point, where noise reduction approaches have been developed to identify nucleosome positions.
Results: In this article, we propose a new approach, termed NucleoFinder, that addresses both the positional heterogeneity across cells and experimental biases by seeking nucleosomes consistently positioned in a cell population and showing a significant enrichment relative to a control sample. Despite the absence of validated dataset, we show that our approach (i) detects fewer false positives than two other nucleosome calling methods and (ii) identifies two important features of the nucleosome organization (the nucleosome spacing downstream of active promoters and the enrichment/depletion of GC/AT dinucleotides at the centre of in vitro nucleosomes) with equal or greater ability than the other two methods.
Availability: The R code of NucleoFinder, an example datafile and instructions are available for download from https://sites.google.com/site/beckerjeremie/
Contact: cholmes@stats.ox.ac.uk
Supplementary information: Supplementary data are available at Bioinformatics online.
doi:10.1093/bioinformatics/bts719
PMCID: PMC3597142  PMID: 23297036
5.  A Gene-Phenotype Network for the Laboratory Mouse and Its Implications for Systematic Phenotyping 
PLoS ONE  2011;6(5):e19693.
The laboratory mouse is the pre-eminent model organism for the dissection of human disease pathways. With the advent of a comprehensive panel of gene knockouts, projects to characterise the phenotypes of all knockout lines are being initiated. The range of genotype-phenotype associations can be represented using the Mammalian Phenotype ontology. Using publicly available data annotated with this ontology we have constructed gene and phenotype networks representing these associations. These networks show a scale-free, hierarchical and modular character and community structure. They also exhibit enrichment for gene coexpression, protein-protein interactions and Gene Ontology annotation similarity. Close association between gene communities and some high-level ontology terms suggests that systematic phenotyping can provide a direct insight into underlying pathways. However some phenotypes are distributed more diffusely across gene networks, likely reflecting the pleiotropic roles of many genes. Phenotype communities show a many-to-many relationship to human disease communities, but stronger overlap at more granular levels of description. This may suggest that systematic phenotyping projects should aim for high granularity annotations to maximise their relevance to human disease.
doi:10.1371/journal.pone.0019693
PMCID: PMC3098258  PMID: 21625554
6.  PlantProm: a database of plant promoter sequences 
Nucleic Acids Research  2003;31(1):114-117.
PlantProm DB, a plant promoter database, is an annotated, non-redundant collection of proximal promoter sequences for RNA polymerase II with experimentally determined transcription start site(s), TSS, from various plant species. The first release (2002.01) of PlantProm DB contains 305 entries including 71, 220 and 14 promoters from monocot, dicot and other plants, respectively. It provides DNA sequence of the promoter regions (−200 : +51) with TSS on the fixed position +201, taxonomic/promoter type classification of promoters and Nucleotide Frequency Matrices (NFM) for promoter elements: TATA-box, CCAAT-box and TSS-motif (Inr). Analysis of TSS-motifs revealed that their composition is different in dicots and monocots, as well as for TATA and TATA-less promoters. The database serves as learning set in developing plant promoter prediction programs. One such program (TSSP) based on discriminant analysis has been created by Softberry Inc. and the application of a support ftp: vector machine approach for promoter identification is under development. PlantProm DB is available at http://mendel.cs.rhul.ac.uk/ and http://www.softberry.com/.
PMCID: PMC165488  PMID: 12519961
7.  Mouse Resource Browser—a database of mouse databases 
The laboratory mouse has become the organism of choice for discovering gene function and unravelling pathogenetic mechanisms of human diseases through the application of various functional genomic approaches. The resulting deluge of data has led to the deployment of numerous online resources and the concomitant need for formalized experimental descriptions, data standardization, database interoperability and integration, a need that has yet to be met. We present here the Mouse Resource Browser (MRB), a database of mouse databases that indexes 217 publicly available mouse resources under 22 categories and uses a standardised database description framework (the CASIMIR DDF) to provide information on their controlled vocabularies (ontologies and minimum information standards), and technical information on programmatic access and data availability. Focusing on interoperability and integration, MRB offers automatic generation of downloadable and re-distributable SOAP application-programming interfaces for resources that provide direct database access. MRB aims to provide useful information to both bench scientists, who can easily navigate and find all mouse related resources in one place, and bioinformaticians, who will be provided with interoperable resources containing data which can be mined and integrated.
Database URL: http://bioit.fleming.gr/mrb
doi:10.1093/database/baq010
PMCID: PMC2911845  PMID: 20627861
8.  EuroPhenome: a repository for high-throughput mouse phenotyping data 
Nucleic Acids Research  2009;38(Database issue):D577-D585.
The broad aim of biomedical science in the postgenomic era is to link genomic and phenotype information to allow deeper understanding of the processes leading from genomic changes to altered phenotype and disease. The EuroPhenome project (http://www.EuroPhenome.org) is a comprehensive resource for raw and annotated high-throughput phenotyping data arising from projects such as EUMODIC. EUMODIC is gathering data from the EMPReSSslim pipeline (http://www.empress.har.mrc.ac.uk/) which is performed on inbred mouse strains and knock-out lines arising from the EUCOMM project. The EuroPhenome interface allows the user to access the data via the phenotype or genotype. It also allows the user to access the data in a variety of ways, including graphical display, statistical analysis and access to the raw data via web services. The raw phenotyping data captured in EuroPhenome is annotated by an annotation pipeline which automatically identifies statistically different mutants from the appropriate baseline and assigns ontology terms for that specific test. Mutant phenotypes can be quickly identified using two EuroPhenome tools: PhenoMap, a graphical representation of statistically relevant phenotypes, and mining for a mutant using ontology terms. To assist with data definition and cross-database comparisons, phenotype data is annotated using combinations of terms from biological ontologies.
doi:10.1093/nar/gkp1007
PMCID: PMC2808931  PMID: 19933761
9.  Models for financial sustainability of biological databases and resources 
Following the technological advances that have enabled genome-wide analysis in most model organisms over the last decade, there has been unprecedented growth in genomic and post-genomic science with concomitant generation of an exponentially increasing volume of data and material resources. As a result, numerous repositories have been created to store and archive data, organisms and material, which are of substantial value to the whole community. Sustained access, facilitating re-use of these resources, is essential, not only for validation, but for re-analysis, testing of new hypotheses and developing new technologies/platforms. A common challenge for most data resources and biological repositories today is finding financial support for maintenance and development to best serve the scientific community. In this study we examine the problems that currently confront the data and resource infrastructure underlying the biomedical sciences. We discuss the financial sustainability issues and potential business models that could be adopted by biological resources and consider long term preservation issues within the context of mouse functional genomics efforts in Europe.
doi:10.1093/database/bap017
PMCID: PMC2790311  PMID: 20157490
10.  MouseBook: an integrated portal of mouse resources 
Nucleic Acids Research  2009;38(Database issue):D593-D599.
The MouseBook (http://www.mousebook.org) databases and web portal provide access to information about mutant mouse lines held as live or cryopreserved stocks at MRC Harwell. The MouseBook portal integrates curated information from the MRC Harwell stock resource, and other Harwell databases, with information from external data resources to provide value-added information above and beyond what is available through other routes such as International Mouse Stain Resource (IMSR). MouseBook can be searched either using an intuitive Google style free text search or using the Mammalian Phenotype (MP) ontology tree structure. Text searches can be on gene, allele, strain identifier (e.g. MGI ID) or phenotype term and are assisted by automatic recognition of term types and autocompletion of gene and allele names covered by the database. Results are returned in a tabbed format providing categorized results identified from each of the catalogs in MouseBook. Individual result lines from each catalog include information on gene, allele, chromosomal location and phenotype, and provide a simple click-through link to further information as well as ordering the strain. The infrastructure underlying MouseBook has been designed to be extensible, allowing additional data sources to be added and enabling other sites to make their data directly available through MouseBook.
doi:10.1093/nar/gkp867
PMCID: PMC2808969  PMID: 19854936
11.  Mouse, man, and meaning: bridging the semantics of mouse phenotype and human disease 
Mammalian Genome  2009;20(8):457-461.
Now that the laboratory mouse genome is sequenced and the annotation of its gene content is improving, the next major challenge is the annotation of the phenotypic associations of mouse genes. This requires the development of systematic phenotyping pipelines that use standardized phenotyping procedures which allow comparison across laboratories. It also requires the development of a sophisticated informatics infrastructure for the description and interchange of phenotype data. Here we focus on the current state of the art in the description of data produced by systematic phenotyping approaches using ontologies, in particular, the EQ (Entity-Quality) approach, and what developments are required to facilitate the linking of phenotypic descriptions of mutant mice to human diseases.
doi:10.1007/s00335-009-9208-3
PMCID: PMC2759022  PMID: 19649761
12.  Tandem and cryptic amino acid repeats accumulate in disordered regions of proteins 
Genome Biology  2009;10(6):R59.
Analysis of amino acid repeats in four mammalian and one bird genome shows that many are associated preferentially with intrinsically unstructured regions.
Background
Amino acid repeats (AARs) are common features of protein sequences. They often evolve rapidly and are involved in a number of human diseases. They also show significant associations with particular Gene Ontology (GO) functional categories, particularly transcription, suggesting they play some role in protein function. It has been suggested recently that AARs play a significant role in the evolution of intrinsically unstructured regions (IURs) of proteins. We investigate the relationship between AAR frequency and evolution and their localization within proteins based on a set of 5,815 orthologous proteins from four mammalian (human, chimpanzee, mouse and rat) and a bird (chicken) genome. We consider two classes of AAR (tandem repeats and cryptic repeats: regions of proteins containing overrepresentations of short amino acid repeats).
Results
Mammals show very similar repeat frequencies but chicken shows lower frequencies of many of the cryptic repeats common in mammals. Regions flanking tandem AARs evolve more rapidly than the rest of the protein containing the repeat and this phenomenon is more pronounced for non-conserved repeats than for conserved ones. GO associations are similar to those previously described for the mammals, but chicken cryptic repeats show fewer significant associations. Comparing the overlaps of AARs with IURs and protein domains showed that up to 96% of some AAR types are associated preferentially with IURs. However, no more than 15% of IURs contained an AAR.
Conclusions
Their location within IURs explains many of the evolutionary properties of AARs. Further study is needed on the types of IURs containing AARs.
doi:10.1186/gb-2009-10-6-r59
PMCID: PMC2718493  PMID: 19486509
13.  Practical application of ontologies to annotate and analyse large scale raw mouse phenotype data 
BMC Bioinformatics  2009;10(Suppl 5):S2.
Background
Large-scale international projects are underway to generate collections of knockout mouse mutants and subsequently to perform high throughput phenotype assessments, raising new challenges for computational researchers due to the complexity and scale of the phenotype data. Phenotypes can be described using ontologies in two differing methodologies. Traditionally an individual phenotypic character has either been defined using a single compound term, originating from a species-specific dedicated phenotype ontology, or alternatively by a combinatorial annotation, using concepts from a range of disparate ontologies, to define a phenotypic character as an entity with an associated quality (EQ). Both methods have their merits, which include the dedicated approach allowing use of community standard terminology, and the combinatorial approach facilitating cross-species phenotypic statement comparisons. Previously databases have favoured one approach over another. The EUMODIC project will generate large amounts of mouse phenotype data, generated as a result of the execution of a set of Standard Operating Procedures (SOPs) and will implement both ontological approaches to capture the phenotype data generated.
Results
For all SOPs a four-tier annotation is made: a high-level description of the SOP, to broadly define the type of data generated by the SOP; individual parameter annotation using the EQ model; annotation of the qualitative data generated for each mouse; and the annotation of mutant lines after statistical analysis. The qualitative assessments of phenodeviance are made at the point of data entry, using child PATO qualities to the parameter quality. To facilitate data querying by scientists more familiar with single compound terms to describe phenotypes, the mappings between the Mammalian Phenotype (MP) ontology and the EQ PATO model are exploited to allow querying via MP terms.
Conclusion
Well-annotated and comparable phenotype databases can be achieved through the use of ontologically derived comparable phenotypic statements and have been implemented here by means of OBO compatible EQ annotations. The implementation we describe also sees scientists working seamlessly with ontologies through the assessment of qualitative phenotypes in terms of PATO qualities and the ability to query the database using community-accepted compound MP terms. This work represents the first time the combinatorial and single-dedicated approaches have both been implemented to annotate a phenotypic dataset.
doi:10.1186/1471-2105-10-S5-S2
PMCID: PMC2679402  PMID: 19426459
14.  Phylogenetic inference under recombination using Bayesian stochastic topology selection 
Bioinformatics  2008;25(2):197-203.
Motivation: Conventional phylogenetic analysis for characterizing the relatedness between taxa typically assumes that a single relationship exists between species at every site along the genome. This assumption fails to take into account recombination which is a fundamental process for generating diversity and can lead to spurious results. Recombination induces a localized phylogenetic structure which may vary along the genome. Here, we generalize a hidden Markov model (HMM) to infer changes in phylogeny along multiple sequence alignments while accounting for rate heterogeneity; the hidden states refer to the unobserved phylogenic topology underlying the relatedness at a genomic location. The dimensionality of the number of hidden states (topologies) and their structure are random (not known a priori) and are sampled using Markov chain Monte Carlo algorithms. The HMM structure allows us to analytically integrate out over all possible changepoints in topologies as well as all the unknown branch lengths.
Results: We demonstrate our approach on simulated data and also to the genome of a suspected HIV recombinant strain as well as to an investigation of recombination in the sequences of 15 laboratory mouse strains sequenced by Perlegen Sciences. Our findings indicate that our method allows us to distinguish between rate heterogeneity and variation in phylogeny caused by recombination without being restricted to 4-taxa data.
Availability: The method has been implemented in JAVA and is available, along with data studied here, from http://www.stats.ox.ac.uk/~webb.
Contact: cholmes@stats.ox.ac.uk
Supplementary information: Supplementary data are available at Bioinformatics online.
doi:10.1093/bioinformatics/btn607
PMCID: PMC2639012  PMID: 19028720
15.  A kinetic core model of the glucose-stimulated insulin secretion network of pancreatic β cells 
Mammalian Genome  2007;18(6-7):508-520.
The construction and characterization of a core kinetic model of the glucose-stimulated insulin secretion system (GSIS) in pancreatic β cells is described. The model consists of 44 enzymatic reactions, 59 metabolic state variables, and 272 parameters. It integrates five subsystems: glycolysis, the TCA cycle, the respiratory chain, NADH shuttles, and the pyruvate cycle. It also takes into account compartmentalization of the reactions in the cytoplasm and mitochondrial matrix. The model shows expected behavior in its outputs, including the response of ATP production to starting glucose concentration and the induction of oscillations of metabolite concentrations in the glycolytic pathway and in ATP and ADP concentrations. Identification of choke points and parameter sensitivity analysis indicate that the glycolytic pathway, and to a lesser extent the TCA cycle, are critical to the proper behavior of the system, while parameters in other components such as the respiratory chain are less critical. Notably, however, sensitivity analysis identifies the first reactions of nonglycolytic pathways as being important for the behavior of the system. The model is robust to deletion of malic enzyme activity, which is absent in mouse pancreatic β cells. The model represents a step toward the construction of a model with species-specific parameters that can be used to understand mouse models of diabetes and the relationship of these mouse models to the human disease state.
Electronic supplementary material
The online version of this article (doi:10.1007/s00335-007-9011-y) contains supplementary material, which is available to authorized users.
doi:10.1007/s00335-007-9011-y
PMCID: PMC1998884  PMID: 17514510
16.  EuroPhenome and EMPReSS: online mouse phenotyping resource 
Nucleic Acids Research  2007;36(Database issue):D715-D718.
EuroPhenome (http://www.europhenome.org) and EMPReSS (http://empress.har.mrc.ac.uk/) form an integrated resource to provide access to data and procedures for mouse phenotyping. EMPReSS describes 96 Standard Operating Procedures for mouse phenotyping. EuroPhenome contains data resulting from carrying out EMPReSS protocols on four inbred laboratory mouse strains. As well as web interfaces, both resources support web services to enable integration with other mouse phenotyping and functional genetics resources, and are committed to initiatives to improve integration of mouse phenotype databases. EuroPhenome will be the repository for a recently initiated effort to carry out large-scale phenotyping on a large number of knockout mouse lines (EUMODIC).
doi:10.1093/nar/gkm728
PMCID: PMC2238991  PMID: 17905814
17.  Understanding Mammalian Genetic Systems: The Challenge of Phenotyping in the Mouse 
PLoS Genetics  2006;2(8):e118.
Understanding mammalian genetic systems is predicated on the determination of the relationship between genetic variation and phenotype. Several international programmes are under way to deliver mutations in every gene in the mouse genome. The challenge for mouse geneticists is to develop approaches that will provide comprehensive phenotype datasets for these mouse mutant libraries. Several factors are critical to success in this endeavour. It will be important to catalogue assay and environment and where possible to adopt standardised procedures for phenotyping tests along with common environmental conditions to ensure comparable datasets of phenotypes. Moreover, the scale of the task underlines the need to invest in technological development improving both the speed and cost of phenotyping platforms. In addition, it will be necessary to develop new informatics standards that capture the phenotype assay as well as other factors, genetic and environmental, that impinge upon phenotype outcome.
doi:10.1371/journal.pgen.0020118
PMCID: PMC1557775  PMID: 16933996
18.  Using ontologies to describe mouse phenotypes 
Genome Biology  2004;6(1):R8.
By combining ontologies from different sources the authors developed a novel approach to describing phenotypes of mutant mice in a standard, structured manner.
The mouse is an important model of human genetic disease. Describing phenotypes of mutant mice in a standard, structured manner that will facilitate data mining is a major challenge for bioinformatics. Here we describe a novel, compositional approach to this problem which combines core ontologies from a variety of sources. This produces a framework with greater flexibility, power and economy than previous approaches. We discuss some of the issues this approach raises.
doi:10.1186/gb-2004-6-1-r8
PMCID: PMC549069  PMID: 15642100
19.  Protein coalitions in a core mammalian biochemical network linked by rapidly evolving proteins 
Background
Cellular ATP levels are generated by glucose-stimulated mitochondrial metabolism and determine metabolic responses, such as glucose-stimulated insulin secretion (GSIS) from the β-cells of pancreatic islets. We describe an analysis of the evolutionary processes affecting the core enzymes involved in glucose-stimulated insulin secretion in mammals. The proteins involved in this system belong to ancient enzymatic pathways: glycolysis, the TCA cycle and oxidative phosphorylation.
Results
We identify two sets of proteins, or protein coalitions, in this group of 77 enzymes with distinct evolutionary patterns. Members of the glycolysis, TCA cycle, metabolite transport, pyruvate and NADH shuttles have low rates of protein sequence evolution, as inferred from a human-mouse comparison, and relatively high rates of evolutionary gene duplication. Respiratory chain and glutathione pathway proteins evolve faster, exhibiting lower rates of gene duplication. A small number of proteins in the system evolve significantly faster than co-pathway members and may serve as rapidly evolving adapters, linking groups of co-evolving genes.
Conclusions
Our results provide insights into the evolution of the involved proteins. We find evidence for two coalitions of proteins and the role of co-adaptation in protein evolution is identified and could be used in future research within a functional context.
doi:10.1186/1471-2148-11-142
PMCID: PMC3112093  PMID: 21612628
20.  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
21.  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
22.  Finding and sharing: new approaches to registries of databases and services for the biomedical sciences 
The recent explosion of biological data and the concomitant proliferation of distributed databases make it challenging for biologists and bioinformaticians to discover the best data resources for their needs, and the most efficient way to access and use them. Despite a rapid acceleration in uptake of syntactic and semantic standards for interoperability, it is still difficult for users to find which databases support the standards and interfaces that they need. To solve these problems, several groups are developing registries of databases that capture key metadata describing the biological scope, utility, accessibility, ease-of-use and existence of web services allowing interoperability between resources. Here, we describe some of these initiatives including a novel formalism, the Database Description Framework, for describing database operations and functionality and encouraging good database practise. We expect such approaches will result in improved discovery, uptake and utilization of data resources.
Database URL: http://www.casimir.org.uk/casimir_ddf
doi:10.1093/database/baq014
PMCID: PMC2911849  PMID: 20627863
23.  XGAP: a uniform and extensible data model and software platform for genotype and phenotype experiments 
Genome Biology  2010;11(3):R27.
XGAP, a software platform for the integration and analysis of genotype and phenotype data.
We present an extensible software model for the genotype and phenotype community, XGAP. Readers can download a standard XGAP (http://www.xgap.org) or auto-generate a custom version using MOLGENIS with programming interfaces to R-software and web-services or user interfaces for biologists. XGAP has simple load formats for any type of genotype, epigenotype, transcript, protein, metabolite or other phenotype data. Current functionality includes tools ranging from eQTL analysis in mouse to genome-wide association studies in humans.
doi:10.1186/gb-2010-11-3-r27
PMCID: PMC2864567  PMID: 20214801
24.  Promoting coherent minimum reporting guidelines for biological and biomedical investigations: the MIBBI project 
Nature biotechnology  2008;26(8):889-896.
The Minimum Information for Biological and Biomedical Investigations (MIBBI) project provides a resource for those exploring the range of extant minimum information checklists and fosters coordinated development of such checklists.
doi:10.1038/nbt.1411
PMCID: PMC2771753  PMID: 18688244

Results 1-24 (24)