The commercialization of bioinformatics

Biological research has experienced a paradigm shift from in vivo or in vitro experimentation to in silico experimentation, a development that relies upon bioinformatics. The beginning of bioinformatics stems from the fortuitous timing of the adoption of new DNA sequencing methods and the availabili...

Descripción completa

Guardado en:
Detalles Bibliográficos
Autor principal: Jones,Phillip B.C.
Lenguaje:English
Publicado: Pontificia Universidad Católica de Valparaíso 2000
Acceso en línea:http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0717-34582000000200002
Etiquetas: Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
Descripción
Sumario:Biological research has experienced a paradigm shift from in vivo or in vitro experimentation to in silico experimentation, a development that relies upon bioinformatics. The beginning of bioinformatics stems from the fortuitous timing of the adoption of new DNA sequencing methods and the availability of mini-and bench-top computers, which became the tools to store and to analyze the sequence data. Another fortunate coincidence was the popularization of the Internet, which provided a means to exchange sequence data and sequence analysis software, and the establishment of the Human Genome Project, which stimulated the need for sophisticated data management and analysis tools. Market pull has rapidly stimulated bioinformatics commercialization as pharmaceutical companies discovered a potential means to cure their innovation deficit. One of the early models for commercializing bioinformatics was simply to sell access to databases of human nucleotide sequencFes. This strategy is heading toward obsolescence as the public consortium nears its goal of sequencing the human genome. The key to future commercialization of sequence data will be to develop informatics technology that transforms this data into information that is useful for diagnosis and therapy. A competitive transformation of sequence data into information will require improvements in data integration and data mining. <A NAME="article"></A>