Evidence map›Paper›PMID 19648136›Full record

ReviewBioinformatics (Oxford, England)2009

Network analyses in systems pharmacology.

Seth I Berger, Ravi Iyengar

Abstract readReview
In one paragraph

Review in Bioinformatics (Oxford, England), 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 221 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
221citing papers in PubMed, 1 pooled it
–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

221 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Multimodal Imaging Reveals Rapid Catecholamine Uptake and Release by Neutrophils.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Article
  4. EHMN2026Metabolites · 2026
    Article
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161 more citing papers are in PubMed but not listed here.

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.

Seth I BergerDepartment of Pharmacology and Systems Therapeutics, Mount Sinai School of Medicine, One Gustave Levy Place, New York, NY 10029, USA.
Ravi Iyengar

Funding

MOLECULAR MECHANISM OF DESENSITIZATIONR01GM054508 · NIGMS · MOUNT SINAI SCHOOL OF MEDICINE OF NYU · PI IYENGAR, SRINIVAS RAVI V · 1995 to 2016
$8.0M
Teaching biomedical and pharmacological trainees to produce FAIR data for AI & ML applicationsT32GM062754 · NIGMS · MOUNT SINAI SCHOOL OF MEDICINE OF NYU · PI SCHLESSINGER, AVNER · 2001 to 2023
$6.2M
STRUCTURE/FUNCTION OF SIGNAL TRANSDUCING COMPONENTSR01DK038761 · NIDDK · MOUNT SINAI SCHOOL OF MEDICINE OF NYU · PI IYENGAR, SRINIVAS RAVI V · 1986 to 2008
$2.4M
NIDDK NIH HHS DK038761NIDDK NIH HHS R01 DK038761NIGMS NIH HHS GM062754NIGMS NIH HHS P50GM07558NIGMS NIH HHS T32 GM062754
6 · The paper itself

Abstract

Systems pharmacology is an emerging area of pharmacology which utilizes network analysis of drug action as one of its approaches. By considering drug actions and side effects in the context of the regulatory networks within which the drug targets and disease gene products function, network analysis promises to greatly increase our knowledge of the mechanisms underlying the multiple actions of drugs. Systems pharmacology can provide new approaches for drug discovery for complex diseases. The integrated approach used in systems pharmacology can allow for drug action to be considered in the context of the whole genome. Network-based studies are becoming an increasingly important tool in understanding the relationships between drug action and disease susceptibility genes. This review discusses how analysis of biological networks has contributed to the genesis of systems pharmacology and how these studies have improved global understanding of drug targets, suggested new targets and approaches for therapeutics, and provided a deeper understanding of the effects of drugs. Taken together, these types of analyses can lead to new therapeutic options while improving the safety and efficacy of existing medications.

Indexed as

Computational BiologyDrug DesignDrug DiscoveryGene Regulatory NetworksSystems Biology

Identifiers

PMID19648136
PMCPMC2752618

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.