Evidence map›Paper›PMID 32872128›Full record

ArticleInternational journal of molecular sciences2020

Bioinformatics Methods in Medical Genetics and Genomics.

Yuriy L Orlov, Ancha V Baranova, Tatiana V Tatarinova

Abstract readEditorial
In one paragraph

Article in International journal of molecular sciences, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
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  3. Article
  4. Article
  5. Article
  6. Recent Trends in Cancer Genomics and Bioinformatics Tools Development.International journal of molecular sciences · 2021
    Article
  7. Article
  8. Article
  9. Article
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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.

Yuriy L OrlovThe Digital Health Institute, I.M. Sechenov First Moscow State Medical University of the Ministry of Health of the Russian Federation (Sechenov University), 119991 Moscow, Russia.ORCID 0000-0003-0587-1609
Ancha V BaranovaSchool of Systems Biology, George Mason University, Fairfax, VA 22030, USA.
Tatiana V TatarinovaLa Verne University, La Verne, CA 91750, USA.ORCID 0000-0003-1787-1112

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Medical genomics relies on next-gen sequencing methods to decipher underlying molecular mechanisms of gene expression. This special issue collects materials originally presented at the "Centenary of Human Population Genetics" Conference-2019, in Moscow. Here we present some recent developments in computational methods tested on actual medical genetics problems dissected through genomics, transcriptomics and proteomics data analysis, gene networks, protein-protein interactions and biomedical literature mining. We have selected materials based on systems biology approaches, database mining. These methods and algorithms were discussed at the Digital Medical Forum-2019, organized by I.M. Sechenov First Moscow State Medical University presenting bioinformatics approaches for the drug targets discovery in cancer, its computational support, and digitalization of medical research, as well as at "Systems Biology and Bioinformatics"-2019 (SBB-2019) Young Scientists School in Novosibirsk, Russia. Selected recent advancements discussed at these events in the medical genomics and genetics areas are based on novel bioinformatics tools.

Indexed as

AlgorithmsComputational BiologyData MiningGenetics, MedicalHigh-Throughput Nucleotide SequencingHumansSystems Biologybioinformaticsgene expressiongenomicshuman population geneticsmedical genetics

Identifiers

PMID32872128
PMCPMC7504073

What Socratic 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 Socratic graph.