Knowlegde Through Fun Welcome To Mady's Site.

Bioinformatics support is essential to the implementation of genome
projects and for public access to their output. Bioinformatics needs
for the genome project fall into two broad areas: (i) databases and
(ii) development of analytical tools. Collection, analysis,
annotation, and storage of the ever increasing amounts of mapping,
sequencing, and expression data in publicly accessible, user-friendly
databases is critical to the project's success. In addition, the
community needs computational methods that will allow scientists to
extract, view, annotate, and analyze genomic information efficiently.
Thus, the genome project must continue to invest substantially in
these areas. Conservation of resources through development of portable
software should be encouraged.
a) Improve content and utility of databases. Databases are the
ultimate repository of genome project's data. As new kinds of data are
generated and new biological relationships discovered, databases must
provide for continuous and rapid expansion and adaptation to the
evolving needs of the scientific community. To encourage broad use,
databases should be responsive to a diverse range of users with
respect to data display, data deposition, data access, and data
analysis. Databases should be structured to allow the queries of
greatest interest to the community to be answered in a seamless way.
Communication among databases must be improved. Achieving this will
require standardization of nomenclature. A database of human genomic
information, analogous to the model organism databases and including
links to many types of phenotypic information, is needed.
b) Develop better tools for data generation, capture, and annotation.
Large-scale, high-throughput genomics centers need readily available,
transportable informatics tools for commonly performed tasks such as
sample tracking, process management, map generation, sequence
finishing, and primary annotation of data. Smaller users urgently need
reliable tools to meet their sequencing and sequence analysis needs.
Readily accessible information about the availability and utility of
various tools should be provided, as well as training in the use of
tools.
c) Develop and improve tools and databases for comprehensive
functional studies. Massive amounts of data on gene expression and
function will be generated in the near future. Databases that can
organize and display this data in useful ways need to be developed.
New statistical and mathematical methods are needed for analysis and
comparison of expression and function data, in a variety of cells and
tissues, at various times and under different conditions. Also needed
are tools for modeling complex networks and interactions.
d) Develop and improve tools for representing and analyzing sequence
similarity and variation. The study of sequence similarity and
variation within and among species will become an increasingly
important approach to biological problems. There will be many forms of
sequence variation, of which SNPs will be only one type. Tools need to
be created for capturing, displaying, and analyzing information about
sequence variation.
e) Create mechanisms to support effective approaches for producing
robust, exportable software that can be widely shared. Many useful
software products are being developed in both academia and industry
that could be of great benefit to the community. However, these tools
generally are not robust enough to make them easily exportable to
another laboratory. Mechanisms are needed for supporting the
validation and development of such tools into products that can be
readily shared and for providing training in the use of these
products. Participation by the private sector is strongly encouraged.