Evidence map›Paper›PMID 24906317›Full record

ReviewMethods in molecular biology (Clifton, N.J.)2014

Introductory review of computational cell cycle modeling.

Andres Kriete, Eishi Noguchi, Christian Sell

Abstract readReview
In one paragraph

Review in Methods in molecular biology (Clifton, N.J.), 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Computational Modeling in Liver Surgery.Frontiers in physiology · 2017
    Review
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

3 authors.

Andres KrieteSchool of Biomedical Engineering, Science and Health Systems, Bossone Research Center, Drexel University, 3141 Chestnut Street, Philadelphia, PA, 19104, USA, andres.kriete@drexel.edu.
Eishi Noguchi
Christian Sell

Funding

Studies of the Swi1-Swi3 Replication Fork Protection ComplexR01GM077604 · NIGMS · DREXEL UNIVERSITY · PI NOGUCHI, EISHI · 2008 to 2012
$1.6M
NIGMS NIH HHS GM0776043NIGMS NIH HHS R01 GM077604
6 · The paper itself

Abstract

Recent advances in the modeling of the cell cycle through computer simulation demonstrate the power of systems biology. By definition, systems biology has the goal to connect a parts list, prioritized through experimental observation or high-throughput screens, by the topology of interactions defining intracellular networks to predict system function. Computer modeling of biological systems is often compared to a process of reverse engineering. Indeed, designed or engineered technical systems share many systems-level properties with biological systems; thus studying biological systems within an engineering framework has proven successful. Here we review some aspects of this process as it pertains to cell cycle modeling.

Indexed as

Cell CycleComputer SimulationModels, BiologicalAnimalsHumansSystems Biology

Identifiers

PMID24906317
PMCPMC4133988

What OpenQuestion holds

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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.