Evidence map›Paper›PMID 20724439›Full record

ArticleNucleic acids research2010

Capturing, sharing and analysing biophysical data from protein engineering and protein characterization studies.

Damien Farrell, Fergal O'Meara, Michael Johnston, John Bradley, Chresten R Søndergaard, Nikolaj Georgi, Helen Webb, Barbara Mary Tynan-Connolly, Una Bjarnadottir, Tommy Carstensen and 1 more

Abstract read
In one paragraph

Article in Nucleic acids research, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

11 authors.

Damien FarrellCentre for Synthesis and Chemical Biology, School of Biomolecular and Biomedical Science, UCD Conway Institute, University College Dublin, Belfield, Dublin 4, Ireland.
Fergal O'Meara
Michael Johnston
John Bradley
Chresten R Søndergaard
Nikolaj Georgi
Helen Webb
Barbara Mary Tynan-Connolly
Una Bjarnadottir
Tommy Carstensen
Jens Erik Nielsen

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Large amounts of data are being generated annually on the connection between the sequence, structure and function of proteins using site-directed mutagenesis, protein design and directed evolution techniques. These data provide the fundamental building blocks for our understanding of protein function, molecular biology and living organisms in general. However, much experimental data are never deposited in databases and is thus 'lost' in journal publications or in PhD theses. At the same time theoretical scientists are in need of large amounts of experimental data for benchmarking and calibrating novel predictive algorithms, and theoretical progress is therefore often hampered by the lack of suitable data to validate or disprove a theoretical assumption. We present PEAT (Protein Engineering Analysis Tool), an application that integrates data deposition, storage and analysis for researchers carrying out protein engineering projects or biophysical characterization of proteins. PEAT contains modules for DNA sequence manipulation, primer design, fitting of biophysical characterization data (enzyme kinetics, circular dichroism spectroscopy, NMR titration data, etc.), and facilitates sharing of experimental data and analyses for a typical university-based research group. PEAT is freely available to academic researchers at http://enzyme.ucd.ie/PEAT.

Indexed as

Protein EngineeringSoftwareBiophysical PhenomenaDatabases, ProteinDNA PrimersKineticsMutagenesisNuclear Magnetic Resonance, BiomolecularPolymerase Chain ReactionProtein ConformationProteinsProtein StabilitySequence Analysis, DNAUser-Computer InterfaceDNA PrimersProteins

Identifiers

PMID20724439
PMCPMC2978379

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.