PIDO: the primary immunodeficiency disease ontology

MOTIVATION: Primary immunodeficiency diseases (PIDs) are Mendelian conditions of high phenotypic complexity and low incidence. They usually manifest in toddlers and infants, although they can also occur much later in life. Information about PIDs is often widely scattered throughout the clinical as well as the research literature and hard to find for both generalists as well as experienced clinicians. Semantic Web technologies coupled to clinical information systems can go some way toward addressing this problem. Ontologies are a central component of such a system, containing and centralizing knowledge about primary immunodeficiencies in both a human- and computer-comprehensible form. The development of an ontology of PIDs is therefore a central step toward developing informatics tools, which can support the clinician in the diagnosis and treatment of these diseases. RESULTS: We present PIDO, the primary immunodeficiency disease ontology. PIDO characterizes PIDs in terms of the phenotypes commonly observed by clinicians during a diagnosis process. Phenotype terms in PIDO are formally defined using complex definitions based on qualities, functions, processes and structures. We provide mappings to biomedical reference ontologies to ensure interoperability with ontologies in other domains. Based on PIDO, we developed the PIDFinder, an ontology-driven software prototype that can facilitate clinical decision support. PIDO connects immunological knowledge across resources within a common framework and thereby enables translational research and the development of medical applications for the domain of immunology and primary immunodeficiency diseases.     

Biodiversity informatics: organizing and linking information across the spectrum of life

Biological knowledge can be inferred from three major levels of information: molecules, organisms and ecologies. Bioinformatics is an established field that has made significant advances in the development of systems and techniques to organize contemporary molecular data; biodiversity informatics is an emerging discipline that strives to develop methods to organize knowledge at the organismal level extending back to the earliest dates of recorded natural history. Furthermore, while bioinformatics studies generally focus on detailed examinations of key 'model' organisms, biodiversity informatics aims to develop over-arching hypotheses that span the entire tree of life. Biodiversity informatics is presented here as a discipline that unifies biological information from a range of contemporary and historical sources across the spectrum of life using organisms as the linking thread. The present review primarily focuses on the use of organism names as a universal metadata element to link and integrate biodiversity data across a range of data sources.     

生物多样性信息学:一个正在兴起的新方向及其关键技术

生物多样性科学和生物信息学是生命科学中两个极为重要也是十分活跃的交叉学科,生物多样性信息学则是目前正在兴起的一个新方向,基发展必将进一步深化信息技术在生物多样性研究中的应用。本文简要介绍了国内外该领域的主要目标与进展,讨论了有关的关键技术（如数据库间的互操作与数字图书馆）,并列出了两个原型系统（Ｓｐｅｃｉｅｓ２０００和ＧＢＩＦ）和其他相关系统的网址。     

geneCBR: a translational tool for multiple-microarray analysis and integrative information retrieval for aiding diagnosis in cancer research

Background  

Bioinformatics and medical informatics are two research fields that serve the needs of different but related communities. Both domains share the common goal of providing new algorithms, methods and technological solutions to biomedical research, and contributing to the treatment and cure of diseases. Although different microarray techniques have been successfully used to investigate useful information for cancer diagnosis at the gene expression level, the true integration of existing methods into day-to-day clinical practice is still a long way off. Within this context, case-based reasoning emerges as a suitable paradigm specially intended for the development of biomedical informatics applications and decision support systems, given the support and collaboration involved in such a translational development. With the goals of removing barriers against multi-disciplinary collaboration and facilitating the dissemination and transfer of knowledge to real practice, case-based reasoning systems have the potential to be applied to translational research mainly because their computational reasoning paradigm is similar to the way clinicians gather, analyze and process information in their own practice of clinical medicine.     

Deciphering next-generation pharmacogenomics: an information technology perspective

In the post-genomic era, the rapid evolution of high-throughput genotyping technologies and the increased pace of production of genetic research data are continually prompting the development of appropriate informatics tools, systems and databases as we attempt to cope with the flood of incoming genetic information. Alongside new technologies that serve to enhance data connectivity, emerging information systems should contribute to the creation of a powerful knowledge environment for genotype-to-phenotype information in the context of translational medicine. In the area of pharmacogenomics and personalized medicine, it has become evident that database applications providing important information on the occurrence and consequences of gene variants involved in pharmacokinetics, pharmacodynamics, drug efficacy and drug toxicity will become an integral tool for researchers and medical practitioners alike. At the same time, two fundamental issues are inextricably linked to current developments, namely data sharing and data protection. Here, we discuss high-throughput and next-generation sequencing technology and its impact on pharmacogenomics research. In addition, we present advances and challenges in the field of pharmacogenomics information systems which have in turn triggered the development of an integrated electronic ‘pharmacogenomics assistant’. The system is designed to provide personalized drug recommendations based on linked genotype-to-phenotype pharmacogenomics data, as well as to support biomedical researchers in the identification of pharmacogenomics-related gene variants. The provisioned services are tuned in the framework of a single-access pharmacogenomics portal.     

Towards recommending visualizations for biodiversity data

To address the critical challenges of biodiversity conservation and study its impact on the ecosystem, over the last decade, scientists have been producing a large amount of highly heterogeneous and distributed data. For managing, processing, and visualizing this data, requires informatics skills. While many biologists lack these skills, informaticians are limited in their understanding of biological domain requirements and the context of the data. The focus of our research study is to assist scientists with the suggestion of possible visualizations for exploring and understanding their data. To be useful, such suggestions need to be based on the visualization knowledge of domain experts. We intend to gather such knowledge and use in the development of a visualization recommendation framework serving the biodiversity research community. Therefore, the authors want to encourage readers to share their domain knowledge on the biodiversity data visualization usage by participating in an online survey.     

Electronic health records: the European scene.

Caring for patients'' health problems relies increasingly on sharing information between clinical departments and disciplines and with managers. The medical record of the future will need to provide a flexible and shareable framework for recording and analysing the consultation process. The advanced informatics in medicine (AIM) programme seeks to encourage research and development in telemedicine in areas that are beyond the scope of any one country. It includes many European projects attempting to define the best storage and transmission formats for such diverse data types as laboratory results, biosignals, x ray images, and photographs, and in clinical specialties varying from intensive care to medicine for elderly people. One example, the good European health record project, is developing a model architecture for computerised health records across Europe that is capable of operating on a wide variety of computer hardwares and will also be able to communicate with many different information systems. The ultimate European health record will be comprehensive and medicolegally acceptable across clinical domains, hold all data types, and be automatically translated between languages.     

Informatics and the Clinical Laboratory

The nature of pathology services is changing under the combined pressures of increasing workloads, cost constraints and technological advancement. In the face of this, laboratory systems need to meet new demands for data exchange with clinical electronic record systems for test requesting and results reporting. As these needs develop, new challenges are emerging especially with respect to the format and content of the datasets which are being exchanged. If the potential for the inclusion of intelligent systems in both these areas is to be realised, the continued dialogue between clinicians and laboratory information specialists is of paramount importance. Requirements of information technology (IT) in pathology, now extend well beyond the provision of purely analytical data. With the aim of achieving seamless integration of laboratory data into the total clinical pathway, ‘Informatics’ – the art and science of turning data into useful information – is becoming increasingly important in laboratory medicine. Informatics is a powerful tool in pathology – whether in implementing processes for pathology modernisation, introducing new diagnostic modalities (e.g. proteomics, genomics), providing timely and evidence-based disease management, or enabling best use of limited and often costly resources. Providing appropriate information to empowered and interested patients – which requires critical assessment of the ever-increasing volume of information available – can also benefit greatly from appropriate use of informatics in enhancing self-management of long term conditions. The increasing demands placed on pathology information systems in the context of wider developmental change in healthcare delivery are explored in this review. General trends in medical informatics are reflected in current priorities for laboratory medicine, including the need for unified electronic records, computerised order entry, data security and recovery, and audit. We conclude that there is a need to rethink the architecture of pathology systems and in particular to address the changed environment in which electronic patient record systems are maturing rapidly. The opportunity for laboratory-based informaticians to work collaboratively with clinical systems developers to embed clinically intelligent decision support systems should not be missed.     

Accessing data from the International Mouse Phenotyping Consortium: state of the art and future plans

The International Mouse Phenotyping Consortium (IMPC) (http://www.mousephenotype.org) will reveal the pleiotropic functions of every gene in the mouse genome and uncover the wider role of genetic loci within diverse biological systems. Comprehensive informatics solutions are vital to ensuring that this vast array of data is captured in a standardised manner and made accessible to the scientific community for interrogation and analysis. Here we review the existing EuroPhenome and WTSI phenotype informatics systems and the IKMC portal, and present plans for extending these systems and lessons learned to the development of a robust IMPC informatics infrastructure.     

Exploring frontiers in the DNA landscape: an introduction to the symposium "Genome Analysis and the Molecular Systematics of Retroelements"

The emerging field of phylogenomics is influencing both the amount and type of characters being brought to bear on long-standing problems in systematic biology. Moreover, the proliferation of sequence information from genome projects in concert with the development of new informatics tools is widening access to comparative data on retroelements to a broad cross section of investigators. Motivated by this, the Society of Systematic Biologists sponsored a symposium entitled "Genome Analysis and the Molecular Systematics of Retroelements," and the resulting papers illustrate this theme of new discoveries and cover three basic areas of research: (i) the taxonomic distribution and phylogenetic structure of families of retroelements; (II) the use of SINE and LINE insertions for phylogenetic inference; and (III) the informatics and classification of repetitive elements. Contributions of each article are briefly discussed in this context and particularly fruitful directions for future research illuminated by results of this symposium are reviewed.     

Open data and algorithms for open science in AI-driven molecular informatics

Recent years have seen a sharp increase in the development of deep learning and artificial intelligence-based molecular informatics. There has been a growing interest in applying deep learning to several subfields, including the digital transformation of synthetic chemistry, extraction of chemical information from the scientific literature, and AI in natural product-based drug discovery. The application of AI to molecular informatics is still constrained by the fact that most of the data used for training and testing deep learning models are not available as FAIR and open data. As open science practices continue to grow in popularity, initiatives which support FAIR and open data as well as open-source software have emerged. It is becoming increasingly important for researchers in the field of molecular informatics to embrace open science and to submit data and software in open repositories. With the advent of open-source deep learning frameworks and cloud computing platforms, academic researchers are now able to deploy and test their own deep learning models with ease. With the development of new and faster hardware for deep learning and the increasing number of initiatives towards digital research data management infrastructures, as well as a culture promoting open data, open source, and open science, AI-driven molecular informatics will continue to grow. This review examines the current state of open data and open algorithms in molecular informatics, as well as ways in which they could be improved in future.     

Marine systems analysis and modeling

Oceanography and marine ecology have a considerable history in the use of computers for modeling both physical and ecological processes. With increasing stress on the marine environment due to human activities such as fisheries and numerous forms of pollution, the analysis of marine problems must increasingly and jointly consider physical, ecological and socio-economic aspects in a broader systems framework that transcends more traditional disciplinary boundaries. This often introduces difficult-to-quantify, “soft” elements, such as values and perceptions, into formal analysis. Thus, the problem domain combines a solid foundation in the physical sciences, with strong elements of ecological, socio-economic and political considerations. At the same time, the domain is also characterized by both a very large volume of some data, and an extremely datapoor situation for other variables, as well as a very high degree of uncertainty, partly due to the temporal and spatial heterogeneity of the marine environment. Consequently, marine systems analysis and management require tools that can integrate these diverse aspects into efficient information systems that can support research as well as planning and also policy- and decisionmaking processes. Supporting scientific research, as well as decision-making processes and the diverse groups and actors involved, requires better access and direct understanding of the information basis as well as easy-to-use, but powerful tools for analysis. Advanced information technology provides the tools to design and implement smart software where, in a broad sense, the emphasis is on the man-machine interface. Symbolic and analogous, graphical interaction, visual representation of problems, integrated data sources, and built-in domain knowledge can effectively support users of complex and complicated software systems. Integration, interaction, visualization and intelligence are key concepts that are discussed in detail, using an operational software example of a coastal water quality model. The model comprises components of a geographical information and mapping system, data bases, dynamic simulation models, and an integrated expert system. An interactive graphical user interface, dynamic visualization of model results, and a hyper-text-based help-and-explain system illustrate some of the features of new and powerful software tools for marine systems analysis and modeling.     

An overview on biodiversity information in databases

The massive development of biodiversity related information systems over the WWW (World Wide Web) has created much excitement in recent years. These arrays of new data sources are counterbalanced by the difficulty in knowing their location and nature. However, biologists and computer scientists have started to pull together in a rising tide of coherence and organization to address this issue. The fledging field of biodiversity informatics is expected to deliver major advances that could turn the WWW into a giant global biodiversity information system. The present paper briefly reviews the databases in preserving the biodiversity data.     

Genome Dashboards: Framework and Examples

Genomics is a sequence-based informatics science and a three-dimensional-structure-based material science. However, in practice, most genomics researchers utilize sequence-based informatics approaches or three-dimensional-structure-based material science techniques, not both. This division is, at least in part, the result of historical developments rather than a fundamental necessity. The underlying computational tools, experimental techniques, and theoretical models were developed independently. The primary result presented here is a framework for the unification of informatics- and physics-based data associated with DNA, nucleosomes, and chromatin. The framework is based on the mathematical representation of geometrically exact rods and the generalization of DNA basepair step parameters. Data unification enables researchers to integrate computational, experimental, and theoretical approaches for the study of chromatin biology. The framework can be implemented using model-view-controller design principles, existing genome browsers, and existing molecular visualization tools. We developed a minimal, web-based genome dashboard, G-Dash-min, and applied it to two simple examples to demonstrate the usefulness of data unification and proof of concept. Genome dashboards developed using the framework and design principles presented here are extensible and customizable and are therefore more broadly applicable than the examples presented. We expect a number of purpose-specific genome dashboards to emerge as a novel means of investigating structure-function relationships for genomes that range from basepairs to entire chromosomes and for generating, validating, and testing mechanistic hypotheses.     

The Mouse Gene Expression Database (GXD)

The Gene Expression Database (GXD) is a community resource of gene expression information for the laboratory mouse. By combining the different types of expression data, GXD aims to provide increasingly complete information about the expression profiles of genes in different mouse strains and mutants, thus enabling valuable insights into the molecular networks that underlie normal development and disease. GXD is integrated with the Mouse Genome Database (MGD). Extensive interconnections with sequence databases and with databases from other species, and the development and use of shared controlled vocabularies extend GXD's utility for the analysis of gene expression information. GXD is accessible through the Mouse Genome Informatics web site at http://www.informatics.jax.org/ or directly at http://www.informatics.jax.org/menus/expression_menu. shtml.     

Synthetic biology of minimal living cells: primitive cell models and semi-synthetic cells

This article summarizes a contribution presented at the ESF 2009 Synthetic Biology focused on the concept of the minimal requirement for life and on the issue of constructive (synthetic) approaches in biological research. The attempts to define minimal life within the framework of autopoietic theory are firstly described, and a short report on the development of autopoietic chemical systems based on fatty acid vesicles, which are relevant as primitive cell models is given. These studies can be used as a starting point for the construction of more complex systems, firstly being inspired by possible origins of life scenarioes (and therefore by considering primitive functions), then by considering an approach based on modern biomacromolecular-encoded functions. At this aim, semi-synthetic minimal cells are defined as those man-made vesicle-based systems that are composed of the minimal number of genes, proteins, biomolecules and which can be defined as living. Recent achievements on minimal sized semi-synthetic cells are then discussed, and the kind of information obtained is recognized as being distinctively derived by a constructive approach. Synthetic biology is therefore a fundamental tool for gaining basic knowledge about biosystems, and it should not be confined at all to the engineering side.     

Mouse tumor biology database (MTB): enhancements and current status

The Mouse Tumor Biology Database (MTB) is a Web-based resource that provides access to information on tumor frequency and latency, genetics and pathology in genetically defined mice (transgenics, targeted mutations and inbred strains). MTB is designed to serve as an information resource for cancer genetics researchers who use the laboratory mouse as a model system for understanding human disease processes. Data in MTB are obtained from the primary scientific literature and direct submissions by the research community. MTB is accessible from the Mouse Genome Informatics Web site (http://www. informatics.jax.org). User support is available for MTB via Email at mgi-help@informatics.jax.org