Evidence map›Paper›PMID 40455154›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2025

Computational Approach for Detection and Analysis of Human-Virus Protein-Protein Interactions.

Ekjot Kaur, Vishal Acharya

Abstract read
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In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Ekjot KaurArtificial Intelligence for Computational Biology (AICoB) Lab, Biotechnology Division, CSIR-Institute of Himalayan Bioresource Technology (CSIR-IHBT), Palampur, Himachal Pradesh, India.
Vishal AcharyaArtificial Intelligence for Computational Biology (AICoB) Lab, Biotechnology Division, CSIR-Institute of Himalayan Bioresource Technology (CSIR-IHBT), Palampur, Himachal Pradesh, India. vishal@ihbt.res.in.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The realm of host-pathogen interactions (HPIs) spans a diverse spectrum of biological occurrences. Within this domain, hosts are represented by both humans and plants, while pathogens encompass a variety of agents, such as viruses, fungi, and bacteria. These interactions serve as foundational elements in the fields of immunology, microbiology, pathology, and medicine. They hold a central role in unveiling the intricate workings of pathogen invasion, host defense mechanisms, and the formulation of strategies for disease prevention and treatment. Computational approaches have emerged as potent tools for studying HPIs, especially in the case of human-virus protein-protein interactions (Hu-Vir PPI), enabling researchers to systematically explore how viruses invade and manipulate host cellular processes. This chapter serves as a comprehensive guide to the computational methods employed for the analysis of Hu-Vir PPI, offering insight into their utility and application.

Indexed as

Computational BiologyHost-Pathogen InteractionsProtein Interaction MappingViral ProteinsVirusesHumansProtein BindingProtein Interaction MapsViral ProteinsArticulation pointsHost–pathogen interactionsHuman–virus protein-protein interactionsNetwork analysisNetwork biologyNetwork bottlenecks

Identifiers

PMID40455154

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.