The status of causality in biological databases: data resources and data retrieval possibilities to support logical modeling.

Causal molecular interactions represent key building blocks used in computational modeling, where they facilitate the assembly of regulatory networks. Logical regulatory networks can be used to predict biological and cellular behaviors by system perturbations and in silico simulations. Today, broad sets of causal interactions are available in a variety of biological knowledge resources. However, different visions, based on distinct biological interests, have led to the development of multiple ways to describe and annotate causal molecular interactions. It can therefore be challenging to efficiently explore various resources of causal interaction and maintain an overview of recorded contextual information that ensures valid use of the data. This review lists the different types of public resources with causal interactions, the different views on biological processes that they represent, the various data formats they use for data representation and storage, and the data exchange and conversion procedures that are available to extract and download these interactions. This may further raise awareness among the targeted audience, i.e. logical modelers and other scientists interested in molecular causal interactions, but also database managers and curators, about the abundance and variety of causal molecular interaction data, and the variety of tools and approaches to convert them into one interoperable resource.

UniBioDicts: Unified access to Biological Dictionaries.

SUMMARY: We present a set of software packages that provide uniform access to diverse biological vocabulary resources that are instrumental for current biocuration efforts and tools. The Unified Biological Dictionaries (UniBioDicts or UBDs) provide a single query-interface for accessing the online API services of leading biological data providers. Given a search string, UBDs return a list of matching term, identifier and metadata units from databases (e.g. UniProt), controlled vocabularies (e.g. PSI-MI) and ontologies (e.g. GO, via BioPortal). This functionality can be connected to input fields (user-interface components) that offer autocomplete lookup for these dictionaries. UBDs create a unified gateway for accessing life science concepts, helping curators find annotation terms across resources (based on descriptive metadata and unambiguous identifiers), and helping data users search and retrieve the right query terms. AVAILABILITY AND IMPLEMENTATION: The UBDs are available through npm and the code is available in the GitHub organisation UniBioDicts (https://github.com/UniBioDicts) under the Affero GPL license. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

The Minimum Information about a Molecular Interaction CAusal STatement (MI2CAST).

MOTIVATION: A large variety of molecular interactions occurs between biomolecular components in cells. When a molecular interaction results in a regulatory effect, exerted by one component onto a downstream component, a so-called 'causal interaction' takes place. Causal interactions constitute the building blocks in our understanding of larger regulatory networks in cells. These causal interactions and the biological processes they enable (e.g. gene regulation) need to be described with a careful appreciation of the underlying molecular reactions. A proper description of this information enables archiving, sharing and reuse by humans and for automated computational processing. Various representations of causal relationships between biological components are currently used in a variety of resources. RESULTS: Here, we propose a checklist that accommodates current representations, called the Minimum Information about a Molecular Interaction CAusal STatement (MI2CAST). This checklist defines both the required core information, as well as a comprehensive set of other contextual details valuable to the end user and relevant for reusing and reproducing causal molecular interaction information. The MI2CAST checklist can be used as reporting guidelines when annotating and curating causal statements, while fostering uniformity and interoperability of the data across resources. AVAILABILITY AND IMPLEMENTATION: The checklist together with examples is accessible at https://github.com/MI2CAST/MI2CAST. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

OLSVis: an animated, interactive visual browser for bio-ontologies.

BACKGROUND: More than one million terms from biomedical ontologies and controlled vocabularies are available through the Ontology Lookup Service (OLS). Although OLS provides ample possibility for querying and browsing terms, the visualization of parts of the ontology graphs is rather limited and inflexible. RESULTS: We created the OLSVis web application, a visualiser for browsing all ontologies available in the OLS database. OLSVis shows customisable subgraphs of the OLS ontologies. Subgraphs are animated via a real-time force-based layout algorithm which is fully interactive: each time the user makes a change, e.g. browsing to a new term, hiding, adding, or dragging terms, the algorithm performs smooth and only essential reorganisations of the graph. This assures an optimal viewing experience, because subsequent screen layouts are not grossly altered, and users can easily navigate through the graph. URL: http://ols.wordvis.com CONCLUSIONS: The OLSVis web application provides a user-friendly tool to visualise ontologies from the OLS repository. It broadens the possibilities to investigate and select ontology subgraphs through a smooth visualisation method.

The gene regulation knowledge commons: the action area of GREEKC.

As computational modeling becomes more essential to analyze and understand biological regulatory mechanisms, governance of the many databases and knowledge bases that support this domain is crucial to guarantee reliability and interoperability of resources. To address this, the COST Action Gene Regulation Ensemble Effort for the Knowledge Commons (GREEKC, CA15205, www.greekc.org) organized nine workshops in a four-year period, starting September 2016. The workshops brought together a wide range of experts from all over the world working on various steps in the knowledge management process that focuses on understanding gene regulatory mechanisms. The discussions between ontologists, curators, text miners, biologists, bioinformaticians, philosophers and computational scientists spawned a host of activities aimed to standardize and update existing knowledge management workflows and involve end-users in the process of designing the Gene Regulation Knowledge Commons (GRKC). Here the GREEKC consortium describes its main achievements in improving this GRKC.

CausalBuilder: bringing the MI2CAST causal interaction annotation standard to the curator.

Molecular causal interactions are defined as regulatory connections between biological components. They are commonly retrieved from biological experiments and can be used for connecting biological molecules together to enable the building of regulatory computational models that represent biological systems. However, including a molecular causal interaction in a model requires assessing its relevance to that model, based on the detailed knowledge about the biomolecules, interaction type and biological context. In order to standardize the representation of this knowledge in 'causal statements', we recently developed the Minimum Information about a Molecular Interaction Causal Statement (MI2CAST) guidelines. Here, we introduce causalBuilder: an intuitive web-based curation interface for the annotation of molecular causal interactions that comply with the MI2CAST standard. The causalBuilder prototype essentially embeds the MI2CAST curation guidelines in its interface and makes its rules easy to follow by a curator. In addition, causalBuilder serves as an original application of the Visual Syntax Method general-purpose curation technology and provides both curators and tool developers with an interface that can be fully configured to allow focusing on selected MI2CAST concepts to annotate. After the information is entered, the causalBuilder prototype produces genuine causal statements that can be exported in different formats.

Gene regulation knowledge commons: community action takes care of DNA binding transcription factors.

A large gap remains between the amount of knowledge in scientific literature and the fraction that gets curated into standardized databases, despite many curation initiatives. Yet the availability of comprehensive knowledge in databases is crucial for exploiting existing background knowledge, both for designing follow-up experiments and for interpreting new experimental data. Structured resources also underpin the computational integration and modeling of regulatory pathways, which further aids our understanding of regulatory dynamics. We argue how cooperation between the scientific community and professional curators can increase the capacity of capturing precise knowledge from literature. We demonstrate this with a project in which we mobilize biological domain experts who curate large amounts of DNA binding transcription factors, and show that they, although new to the field of curation, can make valuable contributions by harvesting reported knowledge from scientific papers. Such community curation can enhance the scientific epistemic process.Database URL: http://www.tfcheckpoint.org.

Jointly creating digital abstracts: dealing with synonymy and polysemy.

BACKGROUND: Ideally each Life Science article should get a 'structured digital abstract'. This is a structured summary of the paper's findings that is both human-verified and machine-readable. But articles can contain a large variety of information types and contextual details that all need to be reconciled with appropriate names, terms and identifiers, which poses a challenge to any curator. Current approaches mostly use tagging or limited entry-forms for semantic encoding. FINDINGS: We implemented a 'controlled language' as a more expressive representation method. We studied how usable this format was for wet-lab-biologists that volunteered as curators. We assessed some issues that arise with the usability of ontologies and other controlled vocabularies, for the encoding of structured information by 'untrained' curators. We take a user-oriented viewpoint, and make recommendations that may prove useful for creating a better curation environment: one that can engage a large community of volunteer curators. CONCLUSIONS: Entering information in a biocuration environment could improve in expressiveness and user-friendliness, if curators would be enabled to use synonymous and polysemous terms literally, whereby each term stays linked to an identifier.

The Arabidopsis leaf as a model system for investigating the role of cell cycle regulation in organ growth.

The role of cell cycle regulation and cell division in plant growth and organ development is controversial. Some experimental data are most easily interpreted from the 'cellular perspective' that cell division drives growth, whereas other observations are more consistent with the 'organismal perspective' that cell division is merely a consequence of growth, and to a large extent facultative. Here we develop a model of cell cycle regulation in the context of leaf development based on literature, published kinematic analysis, flow-cytometric and transcriptomic data obtained from growing Arabidopsis leaves. We tested this model by comparing the in silico inhibition of the cell cycle progression with the experimental observations of transgenic plants overexpressing the cell cycle inhibitor Arath;KRP2. The model simulates the behaviour of proliferating cells quite well, but is inadequate in describing the effects on expanding cells. This may point to a difference in the nature of the expansion process during the proliferating and non-dividing phase of leaf development.

Simulating genetic networks made easy: network construction with simple building blocks.

UNLABELLED: We present SIM-plex, a genetic network simulator with a very intuitive interface in which a user can easily specify interactions as simple 'if-then' statements. The simulator is based on the mathematical model of Piecewise Linear Differential Equations (PLDEs). With PLDEs, genetic interactions are approximated as acting in a switch-like manner. AVAILABILITY: The Java program, examples and a tutorial are available at http://www.psb.ugent.be/cbd/ CONTACT: {stcru,makui}@psb.ugent.be

Genome-wide analysis of gene expression profiles associated with cell cycle transitions in growing organs of Arabidopsis.

Organ growth results from the progression of component cells through subsequent phases of proliferation and expansion before reaching maturity. We combined kinematic analysis, flowcytometry, and microarray analysis to characterize cell cycle regulation during the growth process of leaves 1 and 2 of Arabidopsis (Arabidopsis thaliana). Kinematic analysis showed that the epidermis proliferates until day 12; thereafter, cells expand until day 19 when leaves reach maturity. Flowcytometry revealed that endoreduplication occurs from the time cell division rates decline until the end of cell expansion. Analysis of 10 time points with a 6k-cDNA microarray showed that transitions between the growth stages were closely reflected in the mRNA expression data. Subsequent genome-wide microarray analysis on the three main stages allowed us to categorize known cell cycle genes into three major classes: constitutively expressed, proliferative, and inhibitory. Comparison with published expression data obtained from root zones corresponding to similar developmental stages and from synchronized cell cultures supported this categorization and enabled us to identify a high confidence set of 131 proliferation genes. Most of those had an M phase-dependent expression pattern and, in addition to many known cell cycle-related genes, there were at least 90 that were unknown or previously not associated with proliferation.

The cyclin-dependent kinase inhibitor KRP2 controls the onset of the endoreduplication cycle during Arabidopsis leaf development through inhibition of mitotic CDKA;1 kinase complexes.

Exit from the mitotic cell cycle and initiation of cell differentiation frequently coincides with the onset of endoreduplication, a modified cell cycle during which DNA continues to be duplicated in the absence of mitosis. Although the mitotic cell cycle and the endoreduplication cycle share much of the same machinery, the regulatory mechanisms controlling the transition between both cycles remain poorly understood. We show that the A-type cyclin-dependent kinase CDKA;1 and its specific inhibitor, the Kip-related protein, KRP2 regulate the mitosis-to-endocycle transition during Arabidopsis thaliana leaf development. Constitutive overexpression of KRP2 slightly above its endogenous level only inhibited the mitotic cell cycle-specific CDKA;1 kinase complexes, whereas the endoreduplication cycle-specific CDKA;1 complexes were unaffected, resulting in an increase in the DNA ploidy level. An identical effect on the endoreduplication cycle could be observed by overexpressing KRP2 exclusively in mitotically dividing cells. In agreement with a role for KRP2 as activator of the mitosis-to-endocycle transition, KRP2 protein levels were more abundant in endoreduplicating than in mitotically dividing tissues. We illustrate that KRP2 protein abundance is regulated posttranscriptionally through CDK phosphorylation and proteasomal degradation. KRP2 phosphorylation by the mitotic cell cycle-specific CDKB1;1 kinase suggests a mechanism in which CDKB1;1 controls the level of CDKA;1 activity through regulating KRP2 protein abundance. In accordance with this model, KRP2 protein levels increased in plants with reduced CDKB1;1 activity. Moreover, the proposed model allowed a dynamical simulation of the in vivo observations, validating the sufficiency of the regulatory interactions between CDKA;1, KRP2, and CDKB1;1 in fine-tuning the mitosis-to-endocycle transition.

Transcript profiling of early lateral root initiation.

At the onset of lateral root initiation in Arabidopsis thaliana, the phytohormone auxin activates xylem pole pericycle cells for asymmetric cell division. However, the molecular events leading from auxin to lateral root initiation are poorly understood, in part because the few responsive cells in the process are embedded in the root and are thus difficult to access. A lateral root induction system, in which most xylem pole pericycle cells were synchronously activated by auxin transport inhibition followed by auxin application, was used for microarray transcript profiling. Of 4,600 genes analyzed, 906 significantly differentially regulated genes were identified that could be grouped into six major clusters. Basically, three major patterns were discerned representing induced, repressed, and transiently expressed genes. Analysis of the coregulated genes, which were specific for each time point, provided new insight into the molecular regulation and signal transduction preceding lateral root initiation in Arabidopsis. The reproducible expression profiles during a time course allowed us to define four stages that precede the cell division in the pericycle. These early stages were characterized by G1 cell cycle block, auxin perception, and signal transduction, followed by progression over G1/S transition and G2/M transition. All these processes took place within 6 h after transfer from N-1-naphthylphthalamic acid to 1-naphthalene acetic acid. These results indicate that this lateral root induction system represents a unique synchronized system that allows the systematic study of the developmental program upstream of the cell cycle activation during lateral root initiation.

Versatile gene-specific sequence tags for Arabidopsis functional genomics: transcript profiling and reverse genetics applications.

Microarray transcript profiling and RNA interference are two new technologies crucial for large-scale gene function studies in multicellular eukaryotes. Both rely on sequence-specific hybridization between complementary nucleic acid strands, inciting us to create a collection of gene-specific sequence tags (GSTs) representing at least 21,500 Arabidopsis genes and which are compatible with both approaches. The GSTs were carefully selected to ensure that each of them shared no significant similarity with any other region in the Arabidopsis genome. They were synthesized by PCR amplification from genomic DNA. Spotted microarrays fabricated from the GSTs show good dynamic range, specificity, and sensitivity in transcript profiling experiments. The GSTs have also been transferred to bacterial plasmid vectors via recombinational cloning protocols. These cloned GSTs constitute the ideal starting point for a variety of functional approaches, including reverse genetics. We have subcloned GSTs on a large scale into vectors designed for gene silencing in plant cells. We show that in planta expression of GST hairpin RNA results in the expected phenotypes in silenced Arabidopsis lines. These versatile GST resources provide novel and powerful tools for functional genomics.