Evidence map›Paper›PMID 31979356›Full record

ArticleInternational journal of molecular sciences2020

A Computational Approach for the Prediction of Treatment History and the Effectiveness or Failure of Antiretroviral Therapy.

Olga Tarasova, Nadezhda Biziukova, Dmitry Kireev, Alexey Lagunin, Sergey Ivanov, Dmitry Filimonov, Vladimir Poroikov

Open access · goldAbstract read
PubMed Full text at PMC Publisher
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 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.4field-weighted citation impact, top 24% 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

4 citing papers in PubMed, 18 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Bioinformatics Methods in Medical Genetics and Genomics.International journal of molecular sciences · 2020
    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

7 authors at 3 institutions in 1 country.

Olga TarasovaDepartment of Bioinformatics, Institute of Biomedical Chemistry, 119121 Moscow, Russia.
Nadezhda BiziukovaDepartment of Bioinformatics, Institute of Biomedical Chemistry, 119121 Moscow, Russia.
Dmitry KireevCentral Research Institute of Epidemiology, 111123 Moscow, Russia.
Alexey LaguninDepartment of Bioinformatics, Institute of Biomedical Chemistry, 119121 Moscow, Russia.
Sergey IvanovDepartment of Bioinformatics, Institute of Biomedical Chemistry, 119121 Moscow, Russia.
Dmitry FilimonovDepartment of Bioinformatics, Institute of Biomedical Chemistry, 119121 Moscow, Russia.
Vladimir PoroikovDepartment of Bioinformatics, Institute of Biomedical Chemistry, 119121 Moscow, Russia.
Bioinformatics Institute · RUPirogov Russian National Research Medical University · RUCentral Research Institute of Epidemiology · RU

Funding

Russian Science Foundation 19-75-10097
6 · The paper itself

Abstract

Human Immunodeficiency Virus Type 1 (HIV-1) infection is associated with high mortality if no therapy is provided. Currently, the treatment of an HIV-1 positive patient requires that several drugs should be taken simultaneously. The resistance of the virus to an antiretroviral drug may lead to treatment failure. Our approach focuses on predicting the exposure of a particular viral variant to an antiretroviral drug or drug combination. It also aims at the prediction of drug treatment success or failure. We utilized nucleotide sequences of HIV-1 encoding protease and reverse transcriptase to perform such types of prediction. The PASS (Prediction of Activity Spectra for Substances) algorithm based on the naive Bayesian classifier was used to make a prediction. We calculated the probability of whether a sequence belonged (P

Indexed as

AlgorithmsAnti-HIV AgentsArea Under CurveBayes TheoremDrug Resistance, ViralDrug Therapy, CombinationHIV-1HIV InfectionsHIV ProteaseHIV Protease InhibitorsHIV Reverse TranscriptaseHumansReverse Transcriptase InhibitorsTreatment FailureTreatment OutcomeAnti-HIV AgentsHIV ProteaseHIV Protease InhibitorsHIV Reverse Transcriptasereverse transcriptase, Human immunodeficiency virus 1Reverse Transcriptase InhibitorsHIV-1human immunodeficiency virus Type 1PASSproteaserandom forestreverse transcriptasetherapy failuretreatment history

Identifiers

PMID31979356
PMCPMC7037494
OpenAlexW3002802682

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.