Evidence map›Paper›PMID 41174310›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2026

Using Total Network Dissimilarity to Analyze Protein Structures Across Homologs.

Vasam Manjveekar Prabantu, Vasundhara Gadiyaram, Saraswathi Vishveshwara

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Article in Methods in molecular biology (Clifton, N.J.), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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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

3 authors.

Vasam Manjveekar PrabantuMolecular Biophysics Unit, Indian Institute of Science, Bangalore, Karnataka, India.
Vasundhara GadiyaramMolecular Biophysics Unit, Indian Institute of Science, Bangalore, Karnataka, India.
Saraswathi VishveshwaraMolecular Biophysics Unit, Indian Institute of Science, Bangalore, Karnataka, India. saraswathi@iisc.ac.in.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A novel methodology for comparing protein structural networks (PSNs) of homologous proteins is presented here, leveraging graph spectral analysis and quantitative comparison techniques. The primary objective of this approach is to systematically explore the similarities and differences between homologous protein structures, thereby elucidating the intricate relationships between protein sequence, structure, and function. By employing a combination of network similarity score, total network dissimilarity, and Fiedler vector analysis, this method provides a robust framework for identifying subtle patterns and relationships in protein structure evolution. The insights gained from this approach will contribute significantly to our understanding of protein biology.

Indexed as

Computational BiologyProteinsAlgorithmsDatabases, ProteinProtein ConformationProteinsGraph spectral analysisNetwork connectivityProtein structure networksTotal network dissimilarityWnt proteins

Identifiers

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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.