NSF 00-22
BIOCOMPLEXITY: SPECIAL COMPETITION
Integrated Research to Understand and Model Complexity Among
Biological, Physical, and Social Systems
DEADLINE DATES:
MESSAGE OF INTENT - JANUARY 31, 2000
RESEARCH PROPOSALS - MARCH 1, 2000
INCUBATION ACTIVITIES - MARCH 1, 2000
The following document (nsf0022, replaces nsf9960) is now available from the
NSF Online Document System
Title: Biocomplexity: Special Competition 2000
Type: Program Announcements & Information
Subtype: Biology, Computer/Information Sciences, Crosscutting
Programs, Engineering, Geosciences, Math/Physical
Sciences, NSF-wide, Polar Programs, Social/Behavioral
Sciences
It may be found at:
http://www.nsf.gov/cgi-bin/getpub?nsf0022
Short Description/Synopsis of Program:
This special competition will support integrated research to better
understand and model complexity that arises from the interaction of
biological, physical, and social systems. Biocomplexity arises from dynamics
spanning several levels within a system, between systems, and/or across
multiple spatial (microns to thousands of kilometers) and temporal
(nanoseconds to eons) scales. This special competition will specifically
support Research Projects which directly explore nonlinearities, chaotic
behavior, emergent phenomena or feedbacks within and between systems and/or
integrate across multiple components or scales of time and space in order to
better understand and predict the dynamic behavior of
systems. The competition will also support Incubation Activities that enable
groups of researchers who have not historically collaborated on
biocomplexity research to develop projects via focused workshops, virtual
meetings, and other types of development and planning activities.
NOTE: The Biocomplexity initiative calls for interdisciplinary research. In
particular, CISE researchers are encouraged to collaborate with biologists
and researchers in other fields on solving biocomplexity problems while
advancing the CISE research fields. E.g. (from the annoucement):
"Decades of fruitful research, following the reductionist
paradigm, generated a vast wealth of knowledge about the living
and non-living subcomponents of many environmental systems. Now
researchers from a broad spectrum of fields, armed with
burgeoning databases and a new array of computational,
observational, and analytical tools can undertake the integrative
research necessary to tackle biocomplexity. The study of
biocomplexity offers many challenges to modeling methods,
including mathematical and computational ones. Descriptions of
aggregate behavior, nonlinear phenomena, networks with
distributed or local control, or combinations of continuous and
discrete behavior as well as new visualization methods can be
applied to address biocomplexity. Genome sequencing, DNA-chips,
robotics, computer simulations, new sensors and monitoring
systems, along with satellite-based imaging of the land and seas,
all contribute to the flood of data relevant to the understanding
of biocomplexity. Knowledge discovery techniques (e.g.,
datamining, visualization, summarization, trend extraction, etc.)
are being developed to convert the volumes of data into new
knowledge."
Cognizant Program Officer for
Computer and Information Science and Engineering (CISE):
Y. T. Chien
Phone: (703) 306-1980
E-mail: ytchien@nsf.gov
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