A nice example of an information problem: how to gather a collection of fragments that can jump-start one's understanding of an obviously important topic? There are some tertiary/quaternary summaries that I've encountered, though I haven't done anything very systematic about harvesting them. Here's a recent one:
Nature 1999 Jun 10;399(6736):517-20
It's sink or swim as a tidal wave of data approaches.
Links to web sites that may prove useful:
What Is Bioinformatics? (UC Davis)
The John Hopkins University Bioinformatics Web Server
EMBL - European Bioinformatics Institute
A few links (leading to abstracts) from a PubMed search:
Informatics at the National Institutes of Health: a call to action (Hendee WR)
Medical informatics is defined as the scientific discipline concerned with the systematic processing of data, information and knowledge in medicine and health care. The domain of medical informatics (including health informatics), its aim, methods and tools, and its relevance to other disciplines in medicine and health sciences are outlined. It is recognized that one of the major tasks of medical informatics is modelling processes. (Comput Methods Programs Biomed 1996 Nov;51(3):131-9 A systematic view on medical informatics. Hasman A, Haux R, Albert A)
Preparing for the third millennium: the views of life informatics (Li ZR, Tian AJ, Yang YY)
Structural-functional bioinformatics: knowledge-based NMR interpretation (Kulikowski CA, Zimmerman D, Montelione G, Anderson S)
An ontology for bioinformatics applications (Baker PG, Goble CA, Bechhofer S, Paton NW, Stevens R, Brass A)
Plant genomics (Terryn N, Rouze P, Van Montagu M)
Automated genome sequence analysis and annotation (Andrade MA, Brown NP, Leroy C, Hoersch S, de Daruvar A, Reich C, Franchini A, Tamames J, Valencia A, Ouzounis C, Sander C)
From protein structure to function (Orengo CA, Todd AE, Thornton JM)
Genetic information resources: a new field for medical librarians (Norman F)
The Emerging Importance of Genetics in Epidemiologic Research III. Bioinformatics and statistical genetic methods (Ellsworth DL, Manolio TA)
Bioinformatics in support of molecular medicine (Altman RB)
Molecules to maps: tools for visualization and interaction in support of computational biology (Kraemer ET, Ferrin TE)
And some items from Cambridge Scientific Abstracts:
TI: Bioinformatics takes charge
AU: Lim, HA; Butt, TR
SO: Trends in Biotechnology [TRENDS BIOTECHNOL.], vol. 16, no. 3, pp. 104-107, Mar 1998
AB: The conference series Bioinformatics and Genome Research started in 1990, but it is only quite recently that bioinformatics has attracted a lot of attention and become a buzzword. This conference series has also (unofficially) become the standard for the commercial sector and those academic researchers who are more entrepreneurial in their approach. The boom in bioinformatics and genome research came about partially because of advances in molecular biology and high-throughput sequencing, informed-consumers' demand for a better quality of health care, and the long and expensive drug-discovery cycle. The rapid advances in computer technology are responsible for the revolution in bioinformatics. This includes the collection of biological data that had once been dispersed to cubbyholes and file drawers; these now wend their way into vast databases that, by virtue of their comprehensive nature and instant cross-accessibility, make the information into a commodity more valuable than the sum of its parts. This has brought about sweeping changes in the character of bioinformatics it has passed from being an instrument through which we acquire and manage other information to being itself primary information and a primary asset. As a result, the drug-discovery trade has become very data intensive. 'Bioinformatics', 'computational biology' and 'bioinformation infrastructure' are, strictly, defined as follows: 'bioinformatics' refers to database-like activities involving persistent sets of data that are maintained in a consistent state over essentially indefinite periods of time; 'computational biology' encompasses the use of algorithmic tools to facilitate biological analyses; 'bioinformation infrastructure' comprises the entire collection of information-management systems, analysis tools and communications networks supporting biology. Thus, the last of these may be viewed as a computational scaffold of the first two.
TI: Bioinformatics: From genome data to biological knowledge
AU: Andrade, MA; Sander, C
SO: Current Opinion in Biotechnology [CURR. OPIN. BIOTECHNOL.], vol. 8, no. 6, pp. 675-683, Dec 1997
AB: Recently, molecular biologists have sequenced about a dozen bacterial genomes and the first eukaryotic genome. We can now obtain answers to detailed questions about the complete set of genes of an organism. Bionformatics methods are increasingly used for attaching biological knowledge to long lists of genes, assigning genes to biological pathways, comparing the gene sets of different species, identifying specificity factors, and describing sets of highly conserved proteins common to all domains of life. Substantial progress has recently been made in the availability of primary and added-value databases, in the development of algorithms and of network information services for genome analysis. The pharmaceutical industry has greatly benefited from the accumulation of sequence data through the identification of targets and candidates for the development of drugs, vaccines, diagnostic markers and therapeutic proteins.
TI: Bioinformatics - principles and potential of a new multidisciplinary tool
AU: Benton, David
SO: Trends in Biotechnology [TRENDS BIOTECHNOL], vol. 14, no. 8, pp. 261-272, 1996
AB: The materials of bioinformatics are biological data, and its methods are derived from a wide variety of computational techniques. Recent years have seen an explosive growth in biological data, and the development of novel computational methods. These methods have become essential to research progress in structural biology, genomics, structure-based drug design and molecular evolution. The development and maintenance of a robust infrastructure of biological data is of equal importance if biotechnology is to take maximum advantage of research advances in a wide variety of fields. While bioinformatics has already made important contributions, it faces significant challenges as it matures.
TI: Title The Bioinformatics Bookshelf: Teach Yourself Computational Biology?
AU: Author Pickeral, OK; Boguski, MS
SO: Source CELL -CAMBRIDGE MA-; VOL 96; NUMBER 4; pp. 451-454; 19 Feb 1999