On an infrastructure to support sharing and aggregating pre- and post-publication systems biology research data

The move towards in silico experimentation has resulted in the use of computational models, in addition to traditional experimental models, to generate the raw data that is analysed and published as research findings. This change requires new methods to be introduced to facilitate independent validation of the underlying models and the reported results. The promotion of co-operative research has the potential to help to both validate results and explore wider problem areas. In this paper we leverage and extend two existing software frameworks to develop an infrastructure that has the potential to both promote the sharing of data between researchers pre-publication and enable access to the data for interested parties post-publication. The pre-publication sharing of data would enable larger problem spaces to be explored by distributed research groups; enabling access to the data post-publication would allow reviewers and the wider community to independently verify the published results which would, in the longer term, help to increase confidence in published results. The framework is used to perform reproducible and numerically validated individual-based computational experiments into the onset of colorectal cancer. Existing results are verified and new insights into the top-down versus bottom-up hypothesis of colorectal crypt invasion are given.     

Using multiple ontologies to integrate complex biological data

The strength of the rat as a model organism lies in its utility in pharmacology, biochemistry and physiology research. Data resulting from such studies is difficult to represent in databases and the creation of user-friendly data mining tools has proved difficult. The Rat Genome Database has developed a comprehensive ontology-based data structure and annotation system to integrate physiological data along with environmental and experimental factors, as well as genetic and genomic information. RGD uses multiple ontologies to integrate complex biological information from the molecular level to the whole organism, and to develop data mining and presentation tools. This approach allows RGD to indicate not only the phenotypes seen in a strain but also the specific values under each diet and atmospheric condition, as well as gender differences. Harnessing the power of ontologies in this way allows the user to gather and filter data in a customized fashion, so that a researcher can retrieve all phenotype readings for which a high hypoxia is a factor. Utilizing the same data structure for expression data, pathways and biological processes, RGD will provide a comprehensive research platform which allows users to investigate the conditions under which biological processes are altered and to elucidate the mechanisms of disease.     

The DCCD: A digital data infrastructure for tree-ring research

Existing on-line databases for dendrochronology are not flexible in terms of user permissions, tree-ring data formats, metadata administration and language. This is why we developed the Digital Collaboratory for Cultural Dendrochronology (DCCD). This TRiDaS-based multi-lingual database allows users to control data access, to perform queries, to upload and download (meta)data in a variety of digital formats, and to edit metadata on line. The content of the DCCD conforms to EU best practices regarding the long-term preservation of digital research data.     

Towards a unified data infrastructure to support European and global microbiome research: a call to action

High-quality microbiome research relies on the integrity, management and quality of supporting data. Currently biobanks and culture collections have different formats and approaches to data management. This necessitates a standard data format to underpin research, particularly in line with the FAIR data standards of findability, accessibility, interoperability and reusability. We address the importance of a unified, coordinated approach that ensures compatibility of data between that needed by biobanks and culture collections, but also to ensure linkage between bioinformatic databases and the wider research community.     

Added predictive value of high-throughput molecular data to clinical data and its validation

Hundreds of 'molecular signatures' have been proposed in the literature to predict patient outcome in clinical settings from high-dimensional data, many of which eventually failed to get validated. Validation of such molecular research findings is thus becoming an increasingly important branch of clinical bioinformatics. Moreover, in practice well-known clinical predictors are often already available. From a statistical and bioinformatics point of view, poor attention has been given to the evaluation of the added predictive value of a molecular signature given that clinical predictors or an established index are available. This article reviews procedures that assess and validate the added predictive value of high-dimensional molecular data. It critically surveys various approaches for the construction of combined prediction models using both clinical and molecular data, for validating added predictive value based on independent data, and for assessing added predictive value using a single data set.     

Conference retrospective: An appropriate modeling infrastructure for cancer research

Presentations and discussions at the symposium illustrate some general issues in biomedical modeling for cancer research. Given the motivations for modeling and assumptions concerning who should be involved in the modeling process, one can identify some basic needs to be met in supports to modelers. These concern both the models themselves and ways of presenting them to users. In conclusion, some thoughts are offered on economic and educational issues that may affect the infusion of modeling into biomedical research.     

A workflow to integrate ecological monitoring data from different sources

Programs and initiatives aiming to protect biodiversity and ecosystems have increased over the last decades in response to their decline. Most of these are based on monitoring data to quantitatively describe trends in biodiversity and ecosystems. The estimation of such trends, at large scales, requires the integration of numerous data from multiple monitoring sites. However, due to the high heterogeneity of data formats and the resulting lack of interoperability, the data integration remains sparsely used and synthetic analyses are often limited to a restricted part of the data available.Here we propose a workflow, comprising four main steps, from data gathering to quality control, to better integrate ecological monitoring data and to create a synthetic dataset that will make it possible to analyse larger sets of monitoring data, including unpublished data.The workflow was designed and applied in the production of the Status of Coral Reefs of the World: 2020 report, where more than two hundred individual datasets were integrated to assess the status and trends of hard coral cover at the global scale. The workflow was applied to two case studies and associated R codes, based on the experience acquired during the production of this report.The proposed workflow allows for the integration of datasets with different levels of taxonomic and spatial precision, with a high degree of reproducibility. It provides a conceptual and technical framework for the integration of ecological monitoring data, allowing for the estimation of temporal trends in biodiversity and ecosystems or to test ecological hypotheses at larger scales.     

Time to integrate biotechnological approaches into fish gut microbiome research

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Melatonin in clinical oncology

The aim of this article is provide a survey of the current knowledge relating to the analysis of melatonin and its administration to cancer patients. On the basis of this compilation of data it can be discussed under which conditions melatonin may be used for diagnostic and/or therapeutic purposes in clinical oncology. Melatonin is depressed in patients with cancers of different origins during the phase of primary tumour growth whereas a normal or sometimes elevated pineal melatonin secretory activity is found during early stages of tumour development or when recidivations arise. The clinical studies of Lissoni show that melatonin, particularly if combined with interleukin-2, is able to favourably influence the course of advanced malignant disease leading to a prolonged survival as well as to an improved quality of life. These findings require to be verified by independent and controlled replication studies. If they can be confirmed it should be attempted to administer melatonin to patients with earlier stages of cancer parallel to standard oncological treatment regimens. In such trials it should be tested whether a substitutional therapy in patients with endogenously depressed melatonin may favourably affect the course of the disease both in quantitative (inhibitory effect on tumour growth and spread) and qualitative terms (improved performance status).     

The use of molecular data in mangrove plant research

The use of molecular data in plant studies has increased dramatically duringthe last decade. Recently, molecular techniques have been applied tomangrove plants to investigate population structure and phylogeneticrelationships. We briefly review research on mangrove plants based onprotein polymorphism and DNA data. Results of these molecular studieshave provided new insights into conservation issues, systematics,biogeography, and population biology of mangrove plants, in many casesrevealing unexpected and surprising patterns.     

The clinical application of chronobiology to oncology

The introduction to medical practice of chemical agents for fighting human cancer some 30 years ago brought hope to a field of medicine previously shrouded in despair and impeded by superstition. Gradually more and better agents have become available to the physician and to the patient suffering from cancer. The physician-scientist has, in turn, learned a great deal about normal and abnormal cellular biology by using these drugs as probes. The observations that certain tissues and certain tumors share patterns of drug toxicity have led to a broadening of biologic understanding and to the use of combinations of drugs with shared antitumor activity and unshared toxicities. This empiric art of cancer chemotherapy has resulted in great progress in the treatment of a large number of advanced cancers. As important, however, is that this experience has resulted in knowledge which is leading to the development of rationally designed therapeutic regimens; to drug analogues seeking greater therapeutic-toxic ratios; to the development of methods for chemically interfering with toxic drug effects while allowing or enhancing antitumor effect; and to work defining effects of drug timing. Drug timing research considers drug dosage in respect to the timing of a drug relative to the timing of other drugs (drug-time-drug interactions) or to other doses of that same drug (drug-drug interval); the order of drugs (drug-drug sequence); and the timing of drugs relative to an internal organismic time structure (time-drug interactions). Data in this brief review clearly show that drug timing needs to be considered when designing rational chemotherapy for a living organism suffering from a cancer. The beautiful spatiotemporal complexity of life is not to be ignored or avoided, but should be considered as a golden opportunity to use what few imprecise chemical weapons we have a little more effectively.     

Problems and pitfalls in a clinical research data management system

The problems and pitfalls encountered in the computerized data bank for the Netherlands Coronary Surgery (NCS) study are reviewed. This study involved 848 patients seen before coronary artery surgery and at 1 and 3 yr after surgery. Nineteen data forms were used resulting in maximally 1142 variables per patient. The importance of quality control is emphasized as well as the efficient transfer of information from data bank to statistical processing.     

Antisense therapy in clinical oncology

Nucleic acid molecules have emerged as versatile tools with promising utility as therapeutics for human diseases. The specificity of hybridization of an antisense oligonucleotide (AS ODN) to the target mRNA makes the AS strategy attractive to selectively modulate the expression of genes involved in the pathogenesis of malignant or non-malignant diseases. One AS drug has been approved for local therapy of cytomegalovirus retinitis, and a number of AS ODN are currently tested in clinical trials including ODN that target bcl-2, survivin, and DNA methyltransferase. The clinical studies indicate that AS ODN are well tolerated and may have therapeutic activity. In this overview, we summarize therapeutic concepts, clinical studies, and new promising molecular targets to treat human cancer with AS ODN.     

An overview of clinical molecular genetics

Clinical molecular genetics has recently become recognized as a diagnostic discipline. This article covers the evolution, structure, and possible forward development of clinical molecular genetics. Topics covered include general test categories, introducing new tests, laboratory facilities, staffing and training, and overview of quality issues.