Evidence map›Paper›PMID 27603022›Full record

ArticleCurrent protocols in bioinformatics2016

Tempest: Accelerated MS/MS Database Search Software for Heterogeneous Computing Platforms.

Mark E Adamo, Scott A Gerber

Abstract read
In one paragraph

Article in Current protocols in bioinformatics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

2 authors.

Mark E AdamoNorris Cotton Cancer Center, Geisel School at Dartmouth, Lebanon, New Hampshire.
Scott A GerberNorris Cotton Cancer Center, Geisel School at Dartmouth, Lebanon, New Hampshire.

Funding

Translational phosphoproteomics for lung cancerR01CA155260 · NCI · DARTMOUTH COLLEGE · PI GERBER, SCOTT A. · 2011 to 2015
$1.8M
NCI NIH HHS R01 CA155260
6 · The paper itself

Abstract

MS/MS database search algorithms derive a set of candidate peptide sequences from in silico digest of a protein sequence database, and compute theoretical fragmentation patterns to match these candidates against observed MS/MS spectra. The original Tempest publication described these operations mapped to a CPU-GPU model, in which the CPU (central processing unit) generates peptide candidates that are asynchronously sent to a discrete GPU (graphics processing unit) to be scored against experimental spectra in parallel. The current version of Tempest expands this model, incorporating OpenCL to offer seamless parallelization across multicore CPUs, GPUs, integrated graphics chips, and general-purpose coprocessors. Three protocols describe how to configure and run a Tempest search, including discussion of how to leverage Tempest's unique feature set to produce optimal results. © 2016 by John Wiley & Sons, Inc.

Indexed as

Databases, ProteinSoftwareAlgorithmsComputational BiologyTandem Mass Spectrometrydatabase searchGPGPUmass spectrometryneutral lossOpenCLparallel computingpeptide identificationproteomics

Identifiers

PMID27603022
PMCPMC5736398

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

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.