Evidence map›Paper›PMID 41478993›Full record

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

Evolutionary Insights from Sequence Analysis of Interleukin 17A (IL17A).

Juan C Santos

Abstract read
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In one paragraph

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.

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

1 author.

Juan C SantosDepartment of Biological Sciences, College of Liberal Arts and Sciences, St. John's University, Jamaica, Queens, NY, USA. santosj@stjohns.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Nucleotide sequence analyses provide insights into changes that might have an impact on proteins and their function. With the rapid accumulation of sequence data, it is now possible to recover the evolutionary history of most genes at the population level to species and beyond. Those sequences can be compared for substitutions that might change or not change the encoded protein and its function, but they can also help to estimate evolutionary relationships. These hypotheses, as phylogenetic trees, provide visual and statistical guidance for characterizing the degree of relatedness among biological entities. In a phylogenetic tree, ancestor-descendant relationships are represented by connections, and closely related entities share most of these links, which represent their evolutionary closeness. In this chapter, I outlined a method to retrieve and label nucleotide sequences of the cytokine IL17A gene, align them to identify substitutions in homologous sites, estimate phylogenetic trees with support values, and visualize these trees as images. The methodology outlined here uses free software packages in the R environment and the Python language.

Indexed as

Computational BiologyEvolution, MolecularInterleukin-17Sequence Analysis, DNAHumansPhylogenySequence AlignmentSoftwareInterleukin-17AlignmentAutomatic sequence retrievalHomologyMolecular changesNucleotidesPhylogenetic trees

Identifiers

PMID41478993

What OpenQuestion holds

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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.