Evidence map›Paper›PMID 23514034›Full record

ArticleBMC bioinformatics2013

Computational vaccinology and the ICoVax 2012 workshop.

Yongqun He, Zhiwei Cao, Anne S De Groot, Vladimir Brusic, Christian Schönbach, Nikolai Petrovsky

Abstract readEditorial
In one paragraph

Article in BMC bioinformatics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. 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

6 authors.

Yongqun HeUnit for Laboratory Animal Medicine, Department of Microbiology and Immunology, and Center for Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, MI 48109, USA. yongqunh@umich.edu
Zhiwei Cao
Anne S De Groot
Vladimir Brusic
Christian Schönbach
Nikolai Petrovsky

Funding

TRIAD Scientific Core: TRIAD ToolkitU19AI082642 · NIAID · UNIVERSITY OF RHODE ISLAND · PI PAQUETTE, GREGORY · 2009 to 2013
$13.0M
Ontology-based Information Network to Support Vaccine ResearchR01AI081062 · NIAID · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI HE, YONGQUN · 2009 to 2012
$1.1M
NIAID NIH HHS 1R01AI081062NIAID NIH HHS U19AI082642
6 · The paper itself

Abstract

Computational vaccinology or vaccine informatics is an interdisciplinary field that addresses scientific and clinical questions in vaccinology using computational and informatics approaches. Computational vaccinology overlaps with many other fields such as immunoinformatics, reverse vaccinology, postlicensure vaccine research, vaccinomics, literature mining, and systems vaccinology. The second ISV Pre-conference Computational Vaccinology Workshop (ICoVax 2012) was held on October 13, 2013 in Shanghai, China. A number of topics were presented in the workshop, including allergen predictions, prediction of linear T cell epitopes and functional conformational epitopes, prediction of protein-ligand binding regions, vaccine design using reverse vaccinology, and case studies in computational vaccinology. Although a significant progress has been made to date, a number of challenges still exist in the field. This Editorial provides a list of major challenges for the future of computational vaccinology and identifies developing themes that will expand and evolve over the next few years.

Indexed as

Computational BiologyVaccinesEpitopesEpitopes, T-LymphocyteHumansEpitopesEpitopes, T-LymphocyteVaccines

Identifiers

PMID23514034
PMCPMC3599086

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.