Evidence map›Paper›PMID 11079861›Full record

ArticleProceedings. AMIA Symposium2000

Graphically-enabled integration of bioinformatics tools allowing parallel execution.

K H Cheung, P Miller, A Sherman, S Weston, E Stratmann, M Schultz, M Snyder, A Kumar

Abstract read
In one paragraph

Article in Proceedings. AMIA Symposium, 2000. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

K H CheungCenter for Medical Informatics, Yale University, New Haven, CT, USA.
P Miller
A Sherman
S Weston
E Stratmann
M Schultz
M Snyder
A Kumar

Funding

Global Analysis of Transcription Regulatory NetworksR01CA077808 · NCI · YALE UNIVERSITY · PI SNYDER, MICHAEL P. · 1997 to 2009
$6.8M
IAIMS IMPLEMENTATION AT YALEG08LM005583 · NLM · YALE UNIVERSITY · PI PATON, JOHN A · 1995 to 1999
–
NCI NIH HHS R01 CA77808NLM NIH HHS G08 LM05583
6 · The paper itself

Abstract

Rapid analysis of large amounts of genomic data is of great biological as well as medical interest. This type of analysis will greatly benefit from the ability to rapidly assemble a set of related analysis programs and to exploit the power of parallel computing. TurboGenomics, which is a software package currently in its alpha-testing phase, allows integration of heterogeneous software components to be done graphically. In addition, the tool is capable of making the integrated components run in parallel. To demonstrate these abilities, we use the tool to develop a Web-based application that allows integrated access to a set of large-scale sequence data analysis programs used by a transposon-insertion based yeast genome project. We also contrast the differences in building such an application with and without using the TurboGenomics software.

Indexed as

Computational BiologyGenomicsSoftwareComputer GraphicsComputing MethodologiesGenomeInternetSequence Analysis, DNASystems IntegrationYeasts

Identifiers

PMID11079861
PMCPMC2243957

What OpenQuestion holds

Textmetadata
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.