Evidence map›Paper›PMID 20974283›Full record

ReviewDrug discovery today2011

Understanding infectious agents from an in silico perspective.

Joo Chuan Tong, Lisa F P Ng

Open access · greenAbstract readReview
In one paragraph

Review in Drug discovery today, 2011. 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
0.3field-weighted citation impact, top 41% of its field
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, 4 citations in OpenAlex.

  1. Assessing Uncertainty in A2 Respiratory Syncytial Virus Viral Dynamics.Computational and mathematical methods in medicine · 2015
    Article
  2. Systems biology of fungal infection.Frontiers in microbiology · 2012
    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

2 authors at 2 institutions in 1 country.

Joo Chuan TongData Mining Department, Institute for Infocomm Research, 1 Fusionopolis Way, 21-01 Connexis South Tower, Singapore 138632, Singapore. victor@bic.nus.edu.sg
Lisa F P Ng
Institute for Infocomm Research · SGNational University of Singapore · SG

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Knowledge of infectious diseases now emerging from genomic, proteomic, epidemiological and clinical data can provide insights into the mechanisms of immune function, disease pathogenesis and epidemiology. Here, we describe how considerable advances in computational methods of data mining, mathematical modeling in epidemiology and simulation have been used to enhance our understanding of infectious agents and discuss their impact on the discovery of new therapeutics and controlling their spread.

Indexed as

EpidemicsModels, BiologicalCommunicable DiseasesData MiningEpidemiologic MethodsHumans

Identifiers

PMID20974283
PMCPMC7185741
OpenAlexW2022432707

What OpenQuestion holds

Textmetadata
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.