|
|
| |
Deep computing for the life sciencesVol. 45, No. 3/4, 2001
Order No. G322-0227 |
|
Information technology is playing an increasingly important role in the life sciences. This double issue of the of the IBM Journal of Research and Development, and a companion issue of the IBM Systems Journal, illustrate how the use of a computationally intensive, molecular-based approach is advancing research in the life sciences. The issue contains 14 papers that pertain to molecular structure modeling, genomic and proteomic analysis, protein folding, and drug design. |
 |
| |
|
|
click to enlarge  |
 |
|
|
|
|
|
|
 |
|
|
|
|
|
|
 |
|
HTML PDF ASCII |
|
|
|
|
|
|
 |
|
|
Papers may be viewed by clicking on the title of interest |
|
|
|
|
|
|
 |
|
Preface |
|
William C. Swope, James M. Coffin, and Barry Robson, Guest Editors |
p. 363 |
|
|
|
|
|
|
 |
|
|
|
|
|
|
 |
|
Model studies of the structures, reactivities, and reaction mechanisms of metalloenzymes |
|
K. Morokuma, D. G. Musaev, T. Vreven, H. Basch, M. Torrent, and D. V. Khoroshun |
p. 367 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
DFT-based molecular dynamics as a new tool for computational biology: First applications and perspective |
|
W. Andreoni, A. Curioni, and T. Mordasini |
p. 397 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
Quantum crystallography, a developing area of computational chemistry extending to macromolecules |
|
L. Huang, L. Massa, and J. Karle |
p. 409 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
Interfacing molecular dynamics with continuum dynamics in computer simulation: Toward an application to biological membranes |
|
G. S. D. Ayton, S. Bardenhagen, P. McMurtry, D. Sulsky, and G. A. Voth |
p. 417 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
The adaptive multilevel finite element solution of the Poisson–Boltzmann equation on massively parallel computers |
|
N. A. Baker, D. Sept, M. J. Holst, and J. A. McCammon |
p. 427 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
Brute force estimation of the number of human genes using EST clustering as a measure |
|
D. B. Davison and J. F. Burke |
p. 439 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
Hidden Markov models in biological sequence analysis |
|
E. Birney |
p. 449 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
DELPHI: A pattern-based method for detecting sequence similarity |
|
A. Floratos, I. Rigoutsos, L. Parida, and Y. Gao |
p. 455 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
Evaluating protein structure-prediction schemes using energy landscape theory |
|
M. P. Eastwood, C. Hardin, Z. Luthey-Schulten, and P. G. Wolynes |
p. 475 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
Protein flexibility and electrostatic interactions |
|
S. Kumar, H. J. Wolfson, and R. Nussinov |
p. 499 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
A hierarchical, building-block-based computational scheme for protein structure prediction |
|
C.-J. Tsai, B. Ma, Y. Y. Sham, S. Kumar, H. J. Wolfson, and R. Nussinov |
p. 513 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
Determination of optimal Chebyshev-expanded hydrophobic discrimination function for globular proteins |
|
B. Fain, Y. Xia, and M. Levitt |
p. 525 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
QSAR in grossly underdetermined systems: Opportunities and issues |
|
D. E. Platt, L. Parida, Y. Gao, A. Floratos, and I. Rigoutsos |
p. 533 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
Multiobjective optimization of combinatorial libraries |
|
D. K. Agrafiotis |
p. 545 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
Recent publications by IBM authors |
|
|
p. 567 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
Patents |
|
|
p. 575 |
|
|
|
|
|
|
|
