Evidence map›Paper›PMID 42056696›Full record

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

Feature Frequency Profile (FFP) Method: A Language Model for Whole-Genome ("Organism") Phylogeny.

JaeJin Choi, Byung-Ju Kim, Sung-Hou Kim

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

3 authors.

JaeJin ChoiDepartment of Chemistry and Center for Computational Biology, University of California, Berkeley, CA, USA.
Byung-Ju KimDepartment of Chemistry and Center for Computational Biology, University of California, Berkeley, CA, USA.
Sung-Hou KimDepartment of Chemistry and Center for Computational Biology, University of California, Berkeley, CA, USA. sunghou@berkeley.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

For almost half a century, molecular phylogenetic methods (based on genomic sequence variations among a small number of genes/proteins that are highly homologous among the study population) have dominated in inferring the evolution of diverse organisms despite many important intrinsic limitations. Strictly speaking, these molecular trees represent the inferred evolution of those molecules selected, neither of organisms, nor of whole genomes (as simplified yet quantifiable proxy for the organism) selected. This is primarily because of two reasons: (a) the technology of economic sequencing and assembling the whole genome of an organism did not emerge until recently, especially for eukaryotic whole genomes, and (b) computational methods of comparing whole-genome sequences efficiently did not emerge until recently due to the sparsity of available whole-genome sequences. An example of a whole-genome Tree of Life is presented.

Indexed as

Computational BiologyGenomeGenomicsPhylogenyAnimalsEvolution, MolecularModels, GeneticFeature frequency profile (FFP)Jensen–Shannon divergenceMolecular treeOrganism treePan-genomic Tree-of-Life (ToL)Rooting of ToLWhole-genome tree

Identifiers

PMID42056696

What OpenQuestion holds

Textmetadata
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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.