TY - JOUR
T1 - Biomolecular modeling thrives in the age of technology
AU - Schlick, Tamar
AU - Portillo-Ledesma, Stephanie
N1 - Funding Information:
Support from the National Institutes of Health, National Institutes of General Medical Sciences Awards R01GM055264 and R35-GM122562, NSF RAPID Award (2030377) from the Division of Mathematical Sciences, and Philip-Morris USA Inc. and Philips-Morris International to T.S. are gratefully acknowledged. Computing support from NYU HPC facility and team was instrumental for our own research throughout the decades.
Funding Information:
Support from the National Institutes of Health, National Institutes of General Medical Sciences Awards R01GM055264 and R35-GM122562, NSF RAPID Award (2030377) from the Division of Mathematical Sciences, and Philip-Morris USA Inc. and Philips-Morris International to T.S. are gratefully acknowledged. Computing support from NYU HPC facility and team was instrumental for our own research throughout the decades.
Publisher Copyright:
© 2021, Springer Nature America, Inc.
PY - 2021/5
Y1 - 2021/5
N2 - The biomolecular modeling field has flourished since its early days in the 1970s due to the rapid adaptation and tailoring of state-of-the-art technology. The resulting dramatic increase in size and timespan of biomolecular simulations has outpaced Moore’s law. Here, we discuss the role of knowledge-based versus physics-based methods and hardware versus software advances in propelling the field forward. This rapid adaptation and outreach suggests a bright future for modeling, where theory, experimentation and simulation define three pillars needed to address future scientific and biomedical challenges.
AB - The biomolecular modeling field has flourished since its early days in the 1970s due to the rapid adaptation and tailoring of state-of-the-art technology. The resulting dramatic increase in size and timespan of biomolecular simulations has outpaced Moore’s law. Here, we discuss the role of knowledge-based versus physics-based methods and hardware versus software advances in propelling the field forward. This rapid adaptation and outreach suggests a bright future for modeling, where theory, experimentation and simulation define three pillars needed to address future scientific and biomedical challenges.
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U2 - 10.1038/s43588-021-00060-9
DO - 10.1038/s43588-021-00060-9
M3 - Review article
AN - SCOPUS:85105581616
VL - 1
SP - 321
EP - 331
JO - Nature Computational Science
JF - Nature Computational Science
SN - 2662-8457
IS - 5
ER -