David C. Torney

dblp:44/1217 · DBLP profile ↗
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7ranked-venue papers
0as first author
0since 2021 · last 2005
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Theory of computation · 5Systems, architecture and hardware · 1Applied, interdisciplinary, general and emerging computing · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Theoretical computer science
3 papers
Coding theory · 45% Mathematical optimization · 42% Approximation and online algorithms · 13%
Interdisciplinary, comprehensive, and emerging computing
2 papers
Bioinformatics and computational biology · 100%
Computer architecture, parallel and distributed computing, and storage systems
1 paper
High-performance computing · 77% Parallel and multicore computing · 23%

Topics — the 11 heaviest of 11, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Mathematical optimization
combinatorial optimization
0.122000
Algorithms for optimizing production DNA sequencing · SODA 2000
Greedy Algorithms for Optimized DNA Sequencing · SODA 1999
Bioinformatics and computational biology › genomics
DNA sequencing
0.012000
Algorithms for optimizing production DNA sequencing · SODA 2000
Coding theory › error-correcting codes › combinatorial coding theory › combinatorial codes
DNA codes
0.012000
On similarity codes · IEEE Trans. Inf. Theory 2000
Coding theory › error-correcting codes
nonlinear codes
0.012000
On similarity codes · IEEE Trans. Inf. Theory 2000
Coding theory › error-correcting codes › coding bounds
rate bounds
0.012000
On similarity codes · IEEE Trans. Inf. Theory 2000
Approximation and online algorithms
approximation algorithms
0.011999
Greedy Algorithms for Optimized DNA Sequencing · SODA 1999
Mathematical optimization › combinatorial optimization
greedy algorithm
0.011999
Greedy Algorithms for Optimized DNA Sequencing · SODA 1999
Bioinformatics and computational biology › genomics › genome analysis
genome mapping
0.011990
A parallel computational approach using a cluster of IBM ES/3090 600Js for physical mapping of chromosomes · SC 1990
Bioinformatics and computational biology › genomics › physical mapping
physical mapping of chromosomes
0.011990
A parallel computational approach using a cluster of IBM ES/3090 600Js for physical mapping of chromosomes · SC 1990
High-performance computing
cluster computing
0.011990
A parallel computational approach using a cluster of IBM ES/3090 600Js for physical mapping of chromosomes · SC 1990
Parallel and multicore computing › parallelization strategies › parallel program decomposition
problem partitioning
0.011990
A parallel computational approach using a cluster of IBM ES/3090 600Js for physical mapping of chromosomes · SC 1990

Methods — techniques the papers use, named apart from their topics

sequence similarity measure · 0.0hamming similarity · 0.0greedy algorithm · 0.0parallel fortran · 0.0fragment overlap detection · 0.0
YearPublicationVenuePosition
2005 Equivalence classes of matchings and lattice-square designs
William Y. C. Chen, David C. Torney
Discret. Appl. Math.2
2004 Partition codes
abstract
We introduce the distance concept between two q-ary n-sequences, 2/spl les/q
Arkadii G. D'yachkov, Vyacheslav V. Rykov, David C. Torney, Sergey Yekhanin
ISIT3
2000 Algorithms for optimizing production DNA sequencing
Éva Czabarka, Goran Konjevod, Madhav V. Marathe, Allon G. Percus, David C. Torney
SODA5
2000 On similarity codes
abstract
We introduce a biologically motivated measure of sequence similarity for quaternary N-sequences, extending Hamming similarity. This measure is the sum over the length of the sequences of "alphabetic" similarities at all positions. Alphabetic similarities are defined, symmetrically, on the Cartesian square of the alphabet. These similarities equal zero whenever the two elements differ. In distinction to Hamming similarity, however, our alphabetic similarities take individual values whenever the two elements are identical. In this correspondence we derive lower and upper bounds on the rate of the corresponding quaternary nonlinear and linear codes called similarity codes and applied to DNA sequences.
Arkadii G. D'yachkov, David C. Torney
IEEE Trans. Inf. Theory2
1999 Greedy Algorithms for Optimized DNA Sequencing
Allon G. Percus, David C. Torney
SODA2
1998 Non-adaptive Group Testing in the Presence of Errors
Emanuel Knill, William J. Bruno, David C. Torney
Discret. Appl. Math.3
1990 A parallel computational approach using a cluster of IBM ES/3090 600Js for physical mapping of chromosomes
abstract
A standard technique for mapping a chromosome is to randomly select pieces, to use restriction enzymes to cut these pieces into fragments, and then to use the fragments for estimating the probability of overlap of these pieces. The authors describe a computational approach which has been used in the mapping of human chromosome 16 at Los Alamos National Laboratory. In particular, they describe 6-way and clustered implementations of an IBM Clustered Fortran program for detection of fragment overlap, with specific attention paid to problem partitioning, task structure, synchronization, and other factors which allow this type of code to perform well on a cluster of shared-memory multiprocessors. Measurements for one, six, and twelve processors for reduced problem sizes are included.>
Steven W. White, David C. Torney, Clive C. Whittaker
SC2