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Bioinformatics Information Resources
Evolving Terminology for Emerging Technologies
Comments? Questions? Revisions? 
Mary Chitty MSLS
Last revised July 10, 2019

Poster for BioIT World 2014 

Bioinformatics Information Resources
Mary Chitty, MSLS, Library Director & Taxonomist, Cambridge Healthtech, Needham MA 02494 USA

Biological data is very noisy and disparate, and reproducible results are elusive. More and more, researchers and the pharmaceutical industry are turning to powerful software to interpret genomic, molecular, and clinical information and make meaningful comparisons. The paradox of “big data” is that, as databases grow to sizes that are difficult to manage and parse, even more data is needed – particularly longitudinal data correlating genotypes and phenotypes with clinical outcomes. In this environment, keeping track of where all the data is, how to access it, and monitoring data quality and integrity are often underestimated challenges. Because much useful data is stored as unstructured text, the interoperability of databases relies on disambiguating drug, gene and protein names, and mapping ontologies and taxonomies. This poster lists and annotates valuable resources for tapping the potential of bioinformatics. These include computational tools for analyzing genomic and molecular data, knowledge bases where state-of-the-art research in computational biology is collected, and terminology resources that help diverse databases to communicate with one another, multiplying their discovery potential.

What is bioinformatics? Clinical bioinformatics Translational bioinformatics Expert perspectives and definitions

Key Terminology Resources, Associations, Conferences, Databases, Government Agencies, Journals, Newsletters, and Software

What is bioinformatics?  Expert perspectives and definitions
The definition of bioinformatics is not universally agreed upon. Generally speaking, we define it as the creation and development of advanced information and computational technologies for problems in biology, most commonly molecular biology (but increasingly in other areas of biology). As such, it deals with methods for storing, retrieving and analyzing biological data, such as nucleic acid (DNA/RNA) and protein sequences, structures, functions, pathways and genetic interactions.  Some people construe bioinformatics more narrowly, and include only those issues dealing with the management of genome project sequencing data. Others construe bioinformatics more broadly and include all areas of computational biology, including population modeling and numerical simulations.  Biomedical informatics is a slightly broader umbrella that includes not only bioinformatics, but other areas of informatics in biology, medicine and health-care. They are closely related. Russ Altman in BIoinformatics Methods and Applications, 2008  

Despite the apparent fatigue of the linguistic use of the term itself, bioinformatics has grown perhaps to a point beyond recognition. We explore both historical aspects and future trends and argue that as the field expands, key questions remain unanswered and acquire new meaning while at the same time the range of applications is widening to cover an ever increasing number of biological disciplines. Rise and Demise of Bioinformatics? Promise and Progress, Christos A. Ouzounis, PLOS Computational Biology April 2012

Bioinformatics is the emerging field that deals with the application of computers to the collection, organization, analysis, manipulation, presentation, and sharing of biologic data. A central component of bioinformatics is the study of the best ways to design and operate biologic databases. This is in contrast with the field of computational biology, where specific research questions are the primary focus. Bioinformatics, National Academies Press, 2000

We have coined the term Bioinformatics for the study of informatic processes in biotic systems. Our Bioinformatic approach typically involves spatial, multi- leveled models with many interacting entities whose behavior is determined by local information. Theoretical Biology Group, Univ. of Utrecht, Netherlands, Paulien Hogeweg Director  

clinical bioinformatics: Different from other informatics, clinical bioinformatics should focus more on clinical informatics, including patient complaints, history, therapies, clinical symptoms and signs, physician's examinations, biochemical analyses, imaging profiles, pathologies and other measurements. It was emphasized that the simultaneous evaluation of clinical and basic research could improve medical care, care provision data, and data exploitation methods in disease therapy and algorithms for the analysis of such heterogeneous data sets.  Clinical bioinformatics: a new emerging science Xiangdong Wang and Lance Liotta, Journal of Clinical Bioinformatics 1:1 2011

Translational bioinformatics is the development of storage, analytic, and interpretive methods to optimize the transformation of increasingly voluminous biomedical data, and genomic data, into proactive, predictive, preventive, and participatory health. Translational bioinformatics includes research on the development of novel techniques for the integration of biological and clinical data and the evolution of clinical informatics methodology to encompass biological observations. The end product of translational bioinformatics is newly found knowledge from these integrative efforts that can be disseminated to a variety of stakeholders, including biomedical scientists, clinicians, and patients. AMIA American Medical Informatics Association, Translational bioinformatics

Growth of the bioinformatics literature: articles per year 1984-2013
 growth of GenBank total sequences 1982-2013  

Terminology Resources
Bioinformatics Glossary, Mary Chitty, Genomic Glossaries & Taxonomies

Gene Ontology GO   Bioinformatics initiative with the aim of standardizing the representation of gene and gene product attributes across species and databases. The project provides a controlled vocabulary of terms for describing gene product characteristics and gene product annotation data from GO Consortium members, as well as tools to access and process this data.

HUGO Human Gene Nomenclature Committee is a curated online repository of HGNC-approved gene nomenclature, gene families and associated resources including links to genomic, proteomic and phenotypic information. HUGO is the Human Genome Organization.

Human Phenotype Ontology  Aims to provide a standardized vocabulary of phenotypic abnormalities.  

PubMed MeSH Medical Subject headings computational biology  maps to bioinformatics, and includes genomics, metabolomics and systems biology.


International Society for Computational Biology  Founded 1997. Sponsors the journal Bioinformatics and a number of conferences.

Japanese Society for Bioinformatics

BioIT World  Enabling technologies that are driving biomedical research and the drug development process. 2002-

CSHALS Conference on Semantics in Healthcare and Life Sciences  Use of semantic technologies in the pharmaceutical industry, including hospitals/healthcare institutions and academic research labs. 2008-

Intelligent Systems in Molecular Biology  Annual ISCB meeting 1993-

Pacific Symposium on Biocomputing  Current research in the theory and application of computational methods in problems of biological significance. 1996-

RECOMB Research in Computational Molecular Biology  Scientific forum for theoretical advances in computational biology and their applications in molecular biology and medicine. 1997-

ExPASy, Swiss Institute of Bioinformatics  Resource portal, databases, software tools.  Originally Expert Protein Analysis System

International Nucleotide Sequence Database Collaboration  GenBank, ENA European Nucleotide Archive, DDBJ DNA Databank Japan

Nucleic Acids Research database annual issue

Literature databases include PubMed, Embase and BIOSIS. Patents databases are also relevant, as are electronic medical records.   

Wikipedia, Biological databases

Government Agencies
Big data to knowledge BD2K, NIH BD2K aims to develop the new approaches, standards, methods, tools, software and competencies that will enhance the use of biomedical Big Data by supporting research, implementation and training in data science and other relevant fields.

Biomedical Informatics Research Network  National initiative to advance biomedical research through data sharing and online collaboration. Funded by the National Institute of General Medicine Sciences (NIGMS).

BISTI Biomedical Information Science and Technology Initiative  Consortium of representatives from each of the NIH institutes and centers. Established in 2000 to serve as the focus of biomedical computing issues at the NIH.

ELIXIR European life sciences infrastructure for sharing biological data

Korean Bioinformation Center, KRIBB Core for bioinformatics research.

NCBI National Center for Biotechnology Information, NIH National resource for molecular biology information Part of the National Library of Medicine. Established 1988. Databases, software and more.

Bioinformatics, ISCB, Oxford University Press

BMC Bioinformatics, BioMedCentral 

Briefings in Bioinformatics, Oxford University Press

Journal of Clinical Bioinformatics, BioMedCentral

Molecular Informatics, Wiley

PLOS Computational Biology, Public Library of Science

Bioinform, Genomeweb

BioIT World   Application of informatics, IT and computer science in biomedical research and drug discovery. 

NCBI Sequence analysis tools  Includes BLAST Basic Local Alignment Search Tool.

Open Bioinformatics Foundation Projects include BioJava, Bioperl, BioPython, BioRuby, BioSQL, MOBY.

Wikipedia, Bioinformatics software

Thanks to Aaron Krol, of BioIT World and Clinical Informatics News for valued editorial advice.

Conclusion:  This is a (very selective) work in progress.  Please let me know of your favorite resources to consider adding. 
Mary Chitty


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