Evidence map›Paper›PMID 24592295›Full record

ArticleSystems and synthetic biology2014

A conceptual review on systems biology in health and diseases: from biological networks to modern therapeutics.

Pramod Rajaram Somvanshi, K V Venkatesh

Abstract read
In one paragraph

Article in Systems and synthetic biology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.

0numbers the graph read from it
0cells of the map it votes in
30citing 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

30 citing papers in PubMed.

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  10. Article
  11. Review
  12. Translational Informatics for Natural Products as Antidepressant Agents.Frontiers in cell and developmental biology · 2021
    Review
  13. Tissue/Biofluid Specific Molecular Cartography ofFrontiers in cellular and infection microbiology · 2021
    Article
  14. Article
  15. Pre-Licensure Inter-Professional Perspectives: Pelvic Health Physiotherapy.Physiotherapy Canada. Physiotherapie Canada · 2020
    Article
  16. Article
  17. Article
  18. Review
  19. Review
  20. 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.

Pramod Rajaram SomvanshiBiosystems Engineering, Department of Chemical Engineering, Indian Institute of Technology Bombay, Powai, Mumbai, 400076 Maharashtra India.
K V VenkateshBiosystems Engineering, Department of Chemical Engineering, Indian Institute of Technology Bombay, Powai, Mumbai, 400076 Maharashtra India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Human physiology is an ensemble of various biological processes spanning from intracellular molecular interactions to the whole body phenotypic response. Systems biology endures to decipher these multi-scale biological networks and bridge the link between genotype to phenotype. The structure and dynamic properties of these networks are responsible for controlling and deciding the phenotypic state of a cell. Several cells and various tissues coordinate together to generate an organ level response which further regulates the ultimate physiological state. The overall network embeds a hierarchical regulatory structure, which when unusually perturbed can lead to undesirable physiological state termed as disease. Here, we treat a disease diagnosis problem analogous to a fault diagnosis problem in engineering systems. Accordingly we review the application of engineering methodologies to address human diseases from systems biological perspective. The review highlights potential networks and modeling approaches used for analyzing human diseases. The application of such analysis is illustrated in the case of cancer and diabetes. We put forth a concept of cell-to-human framework comprising of five modules (data mining, networking, modeling, experimental and validation) for addressing human physiology and diseases based on a paradigm of system level analysis. The review overtly emphasizes on the importance of multi-scale biological networks and subsequent modeling and analysis for drug target identification and designing efficient therapies.

Indexed as

Biological networksGenotypePhenotypeSystems biologySystems engineering

Identifiers

PMID24592295
PMCPMC3933630

What OpenQuestion holds

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Registered trials

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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.