Evidence map›Paper›PMID 39553947›Full record

ArticlebioRxiv : the preprint server for biology2025

Decoding the Functional Interactome of Non-Model Organisms with PHILHARMONIC.

Samuel Sledzieski, Charlotte Versavel, Rohit Singh, Faith Ocitti, Kapil Devkota, Lokender Kumar, Polina Shpilker, Liza Roger, Jinkyu Yang, Nastassja Lewinski and 4 more

Abstract readPreprint
PubMed Full text at PMC Publisher
In one paragraph

Article in bioRxiv : the preprint server for biology, 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

14 authors.

Samuel SledzieskiCenter for Computational Biology, Flatiron Institute, New York, NY, USA.ORCID 0000-0002-0170-3029
Charlotte VersavelDepartment of Computer Science, Tufts University, Medford MA, USA.
Rohit SinghDepartments of Biostatistics & Bioinformatics and Cell Biology, Duke University, Durham, NC, USA.ORCID 0000-0002-4084-7340
Faith OcittiDepartment of Computer Science, Tufts University, Medford MA, USA.
Kapil DevkotaDepartments of Biostatistics & Bioinformatics and Cell Biology, Duke University, Durham, NC, USA.ORCID 0000-0002-6093-6260
Lokender KumarShoolini University, Solan, Himachal Pradesh-173229- India.ORCID 0000-0002-0692-0137
Polina ShpilkerDepartment of Computer Science, Tufts University, Medford MA, USA.ORCID 0000-0002-6761-7326
Liza RogerSchool of Molecular Sciences, Arizona State University, Phoenix, AZ, USA.ORCID 0000-0003-2274-8311
Jinkyu YangDepartment of Mechanical Engineering, Seoul National University, Seoul, South Korea.ORCID 0000-0003-1547-0219
Nastassja LewinskiDepartment of Chemical and Life Science Engineering, Virginia Commonwealth University, Richmond, VA, USA.ORCID 0000-0002-9335-9949
Hollie PutnamDepartment of Biological Sciences, University of Rhode Island, Kingston, RI, USA.ORCID 0000-0003-2322-3269
Judith Klein-SeetharamanSchool of Molecular Sciences, Arizona State University, Phoenix, AZ, USA.ORCID 0000-0002-4892-6828
Bonnie BergerComputer Science & Artificial Intelligence Laboratory and Department of Mathematics, MIT Cambridge, MA, USA.
Lenore CowenDepartment of Computer Science, Tufts University, Medford MA, USA.ORCID 0000-0001-6698-6413

Funding

Manifold representations and active learning for 21 st century biologyR35GM141861 · NIGMS · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI BERGER, BONNIE · 2021 to 2025
$1.9M
NIGMS NIH HHS R35 GM141861
6 · The paper itself

Abstract

Despite the widespread availability of genome sequencing pipelines, many genes remain part of the genome's "dark matter," where existing inference tools cannot even begin to guess the biological function of their proteins from sequence alone. This challenge is especially pronounced in organisms that are highly evolutionarily distant from well-studied models, where homology-based methods break down. Here, we describe PHILHARMONIC, a computational method that combines deep learning-based

Identifiers

PMID39553947
PMCPMC11565725

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.