Evidence map›Paper›PMID 31247973›Full record

ArticleMolecules (Basel, Switzerland)2019

Molecular Computing and Bioinformatics.

Xin Liang, Wen Zhu, Zhibin Lv, Quan Zou

Open access · goldAbstract readEditorial
In one paragraph

Article in Molecules (Basel, Switzerland), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
0.8field-weighted citation impact, top 29% 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

12 citing papers in PubMed, 28 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. Article
  5. In silico prospection of Lactobacillus acidophilus strains with potential probiotic activity.Brazilian journal of microbiology : [publication of the Brazilian Society for Microbiology] · 2023
    Article
  6. Article
  7. Article
  8. Article
  9. Review
  10. Review
  11. Review
  12. 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

4 authors at 2 institutions in 1 country.

Xin LiangSchool of Mathematics and Statistics, Hainan Normal University, Haikou 570100, China.
Wen ZhuSchool of Mathematics and Statistics, Hainan Normal University, Haikou 570100, China.
Zhibin LvInstitute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu 610054, China. lvzhibin@pku.edu.cn.
Quan ZouInstitute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu 610054, China. zouquan@nclab.net.ORCID 0000-0001-6406-1142
Hainan Normal University · CNUniversity of Electronic Science and Technology of China · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Molecular computing and bioinformatics are two important interdisciplinary sciences that study molecules and computers. Molecular computing is a branch of computing that uses DNA, biochemistry, and molecular biology hardware, instead of traditional silicon-based computer technologies. Research and development in this area concerns theory, experiments, and applications of molecular computing. The core advantage of molecular computing is its potential to pack vastly more circuitry onto a microchip than silicon will ever be capable of-and to do it cheaply. Molecules are only a few nanometers in size, making it possible to manufacture chips that contain billions-even trillions-of switches and components. To develop molecular computers, computer scientists must draw on expertise in subjects not usually associated with their field, including organic chemistry, molecular biology, bioengineering, and smart materials. Bioinformatics works on the contrary; bioinformatics researchers develop novel algorithms or software tools for computing or predicting the molecular structure or function. Molecular computing and bioinformatics pay attention to the same object, and have close relationships, but work toward different orientations.

Indexed as

Computational BiologyComputers, MolecularDrug DevelopmentDrug DiscoveryHumansResearchbioinformaticsbio-inspiredDNAdrugmachine learningmolecular computingproteinRNA

Identifiers

PMID31247973
PMCPMC6651761
OpenAlexW2953967261

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.