Evidence map›Paper›PMID 42397292›Full record

ArticleJournal of chemical information and modeling2026

QSAR in the Browser: An Interactive Cheminformatics Web Application.

Syed Zayyan Masud, Theo Redfern-Nichols, Taufiq Rahman, Graham Ladds

Abstract read
In one paragraph

Article in Journal of chemical information and modeling, 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

4 authors.

Syed Zayyan MasudDepartment of Pharmacology, University of Cambridge, Tennis Court Road, CambridgeCB2 1PD, U.K.ORCID 0009-0004-7039-5121
Theo Redfern-NicholsDepartment of Pharmacology, University of Cambridge, Tennis Court Road, CambridgeCB2 1PD, U.K.
Taufiq RahmanDepartment of Pharmacology, University of Cambridge, Tennis Court Road, CambridgeCB2 1PD, U.K.ORCID 0000-0003-3830-5160
Graham LaddsDepartment of Pharmacology, University of Cambridge, Tennis Court Road, CambridgeCB2 1PD, U.K.ORCID 0000-0001-7320-9612

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cheminformatic analysis has been an active field for almost half a century, with considerable innovation accelerating drug discovery. However, the requirement for programming expertise prevents its popular use, often necessitating collaboration between multiple disciplines to integrate cheminformatics tasks into drug discovery pipelines. Various efforts have been made to mitigate this issue at the cost of cross-platform compatibility and preservation of data privacy. We introduce a static web application, QSAR, Quantitative Structure-Activity Relationship In The Browser (QITB), that performs various cheminformatic analyses on the user's device, with no external server required. It includes tools to access the publicly available ChEMBL database and tools for users to upload their own data. It automatically processes data, offers a range of interactive tools for data visualization and analysis, and supports the training and evaluation of lightweight machine-learning models. By being hosted on GitHub Pages, the QITB web app is broadly accessible and enables the use of cheminformatics by experts and nonexperts alike.

Indexed as

CheminformaticsDrug DiscoveryQuantitative Structure-Activity RelationshipInternetMachine LearningUser-Computer Interface

Identifiers

PMID42397292
PMCPMC13417879

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.