Facilitating the development of controlled vocabularies for metabolomics technologies with text mining

BACKGROUND: Many bioinformatics applications rely on controlled vocabularies or ontologies to consistently interpret and seamlessly integrate information scattered across public resources. Experimental data sets from metabolomics studies need to be integrated with one another, but also with data produced by other types of omics studies in the spirit of systems biology, hence the pressing need for vocabularies and ontologies in metabolomics. However, it is time-consuming and non trivial to construct these resources manually. RESULTS: We describe a methodology for rapid development of controlled vocabularies, a study originally motivated by the needs for vocabularies describing metabolomics technologies. We present case studies involving two controlled vocabularies (for nuclear magnetic resonance spectroscopy and gas chromatography) whose development is currently underway as part of the Metabolomics Standards Initiative. The initial vocabularies were compiled manually, providing a total of 243 and 152 terms. A total of 5,699 and 2,612 new terms were acquired automatically from the literature. The analysis of the results showed that full-text articles (especially the Materials and Methods sections) are the major source of technology-specific terms as opposed to paper abstracts. CONCLUSIONS: We suggest a text mining method for efficient corpus-based term acquisition as a way of rapidly expanding a set of controlled vocabularies with the terms used in the scientific literature. We adopted an integrative approach, combining relatively generic software and data resources for time- and cost-effective development of a text mining tool for expansion of controlled vocabularies across various domains, as a practical alternative to both manual term collection and tailor-made named entity recognition methods

G2Cdb: the Genes to Cognition database

Neuroscience databases linking genes, proteins, (patho)physiology, anatomy and behaviour across species will be valuable in a broad range of studies of the nervous system. G2Cdb is such a neuroscience database aiming to present a global view of the role of synapse proteins in physiology and disease. G2Cdb warehouses sets of genes and proteins experimentally elucidated by proteomic mass spectroscopy of signalling complexes and proteins biochemically isolated from mammalian synapse preparations, giving an experimentally validated definition of the constituents of the mammalian synapse. Using automated text-mining and expert (human) curation we have systematically extracted information from published neurobiological studies in the fields of synaptic signalling electrophysiology and behaviour in knockout and other transgenic mice. We have also surveyed the human genetics literature for associations to disease caused by mutations in synaptic genes. The synapse proteome datasets that G2Cdb provides offer a basis for future work in synapse biology and provide useful information on brain diseases. They have been integrated in a such way that investigators can rapidly query whether a gene or protein is found in brain-signalling complex(es), has a phenotype in rodent models or whether mutations are associated with a human disease. G2Cdb can be freely accessed at http://www.genes2cognition.org

Building bridges between cellular and molecular structural biology

The integration of cellular and molecular structural data is key to understanding the function of macromolecular assemblies and complexes in their in vivo context. Here we report on the outcomes of a workshop that discussed how to integrate structural data from a range of public archives. The workshop identified two main priorities: the development of tools and file formats to support segmentation (that is, the decomposition of a three-dimensional volume into regions that can be associated with defined objects), and the development of tools to support the annotation of biological structures.Peer reviewe

Chemical information matters: an e-Research perspective on information and data sharing in the chemical sciences

Recently, a number of organisations have called for open access to scientific information and especially to the data obtained from publicly funded research, among which the Royal Society report and the European Commission press release are particularly notable. It has long been accepted that building research on the foundations laid by other scientists is both effective and efficient. Regrettably, some disciplines, chemistry being one, have been slow to recognise the value of sharing and have thus been reluctant to curate their data and information in preparation for exchanging it. The very significant increases in both the volume and the complexity of the datasets produced has encouraged the expansion of e-Research, and stimulated the development of methodologies for managing, organising, and analysing "big data". We review the evolution of cheminformatics, the amalgam of chemistry, computer science, and information technology, and assess the wider e-Science and e-Research perspective. Chemical information does matter, as do matters of communicating data and collaborating with data. For chemistry, unique identifiers, structure representations, and property descriptors are essential to the activities of sharing and exchange. Open science entails the sharing of more than mere facts: for example, the publication of negative outcomes can facilitate better understanding of which synthetic routes to choose, an aspiration of the Dial-a-Molecule Grand Challenge. The protagonists of open notebook science go even further and exchange their thoughts and plans. We consider the concepts of preservation, curation, provenance, discovery, and access in the context of the research lifecycle, and then focus on the role of metadata, particularly the ontologies on which the emerging chemical Semantic Web will depend. Among our conclusions, we present our choice of the "grand challenges" for the preservation and sharing of chemical information

The doctoral research abstract. Vol:9 2016 / Institute of Graduate Studies, UiTM

FOREWORD: Seventy three doctoral graduands will be receiving their scroll today signifying their achievements in completing their PhD journey. The novelty of their research is shared with you through The Doctoral Abstracts on this auspicious occasion, UiTM 84th Convocation. We are indeed proud that another 73 scholarly contributions to the world of knowledge and innovation have taken place through their doctoral research ranging from Science and Technology, Business and Administration, and Social Science and Humanities. As we rejoice and celebrate your achievement, we would like to acknowledge dearly departed Dr Halimi Zakaria’s scholarly contribution entitled “Impact of Antecedent Factors on Collaborative Technologies Usage among Academic Researchers in Malaysian Research Universities”. He has left behind his discovery to be used by other researchers in their quest of pursuing research in the same area, a discovery that his family can be proud of. Graduands, earning your PhD is not the end of discovering new ideas, invention or innovation but rather the start of discovering something new. Enjoy every moment of its discovery and embrace that life is full of mystery and treasure that is waiting for you to unfold. As you unfold life’s mystery, remember you have a friend to count on, and that friend is UiTM. Congratulations for completing this academic journey. Keep UiTM close to your heart and be our ambassador wherever you go. / Prof Emeritus Dato’ Dr Hassan Said Vice Chancellor Universiti Teknologi MAR

Supporting the diagnosis of childhood brain tumours through structural reports and ontological reasoning

After Leukaemia, childhood brain tumours are the second most common form of cancer. The most accurate way to diagnosis a tumour is via a biopsy, but is not always possible. An alternative is Magnetic Resonance Spectroscopy (MRS) which analyses the chemical make-up of tissue and then used to make a diagnosis. A patient's medical records are an important part of treatment, used to communicate findings from medical images. However, these are written using unclear and ambiguous free text. A solution is to produce records using Structured Reporting. This has been incorporated into the Digital Communications in Medicine (DICOM) Standard for established imaging modalities, but not for MRS. An ontology was modelled to produce DICOM supported Structured Reports for MRS. Also, an algorithm to diagnosis different types of childhood brain cancer using MRS spectra was incorporated, allowing automated diagnostic support. A prototype Structured Reporting application was designed based on the ontology. The ontology was able to produce Structured Reports that successfully diagnosed certain childhood brain tumours based on the MRS readings. Usability testing and the diagnostic aspect of the ontology garnered positive feedback as MRS data is only currently used to diagnosis whether the tissue is cancerous or not

Cutting Edge: Building bridges between cellular and molecular structural biology

The integration of cellular and molecular structural data is key to understanding the function of macromolecular assemblies and complexes in their in vivo context. Here we report on the outcomes of a workshop that discussed how to integrate structural data from a range of public archives. The workshop identified two main priorities: the development of tools and file formats to support segmentation (that is, the decomposition of a three-dimensional volume into regions that can be associated with defined objects), and the development of tools to support the annotation of biological structures