Evidence map›Paper›PMID 40661633›Full record

ArticlebioRxiv : the preprint server for biology2025

A network model for patient-derived drug response in breast cancer integrating multi-omics datasets.

Banabithi Bose, Barbara Stranger, Serdar Bozdag

Abstract readPreprint
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

3 authors.

Banabithi BoseDepartment of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, Colorado.ORCID 0000-0003-0842-8768
Barbara StrangerDepartment of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, Colorado.ORCID 0000-0001-9021-7331
Serdar BozdagDept. of Computer Science and Engineering, University of North Texas, Denton, TX 76203.ORCID 0000-0002-4813-4310

Funding

lntegrating multi-omics datasets to infer phenotype-specific driver genes, regulatory interactions and drug responseR35GM133657 · NIGMS · UNIVERSITY OF NORTH TEXAS · PI Serdar Bozdag · 2019 to 2026
$3.1M
Genetic mechanisms underlying sexual dimorphism in cancer and response to therapyR01CA229618 · NCI · UNIVERSITY OF COLORADO DENVER · PI HUANG, RONG STEPHANIE, STRANGER, BARBARA E · 2019 to 2024
$2.9M
NCI NIH HHS R01 CA229618NIGMS NIH HHS R35 GM133657
6 · The paper itself

Abstract

The widespread availability of multi-omics tumor profiling has enabled detailed molecular characterization of individual tumors, paving the way for more effective, less toxic, and patient-specific therapies. However, widespread compound screens in human patients are constrained by ethical and logistical challenges, underscoring the need for computational models capable of predicting

Identifiers

PMID40661633
PMCPMC12259075

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.