Publication2025
A Machine Learning-Driven Approach to Identify Phytochemical Inhibitors of the Pseudomonas aeruginosa Quorum Sensing Regulator LasR
The record
- Type
- Publication
- Date
- 1 January 2025
- Level
- National
- Journal
- 2025 5th IEEE International Conference on Applied Electromagnetics Signal Processing and Communication Aespc 2025
- Published
- 1 January 2025
- DOI
- 10.1109/aespc67542.2025.11326730
- Scopus ID
- 105033156505
- Authors
- 5
- Open access
- No
- Citations
- 0
- International co-authorship
- No
- Co-author countries
- IN
Classification
Every label below carries the reasoning it was assigned on, the confidence band it was assigned in, and what produced it. The rubric is published.
UN Sustainable Development Goals
3.3 End the epidemics of AIDS, tuberculosis, malaria, neglected tropical diseases, hepatitis and water-borne diseases
Machine learning model identifies phytochemical inhibitors of Pseudomonas aeruginosa quorum sensing LasR, addressing antimicrobial resistance through disruption of biofilm formation mechanisms.
- High confidence
- The subject matter is a strong and direct inference from the record type, the funding or organising body, or the programme context, even where the title alone is thin. Example: an ICMR-funded project against SDG 3, on the strength of the agency.
- Judged
- Judged against the published classification rubric, under the rubric and prompt versions recorded with the run that produced it.
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
9.5 Enhance scientific research, upgrade technological capabilities, and increase researchers and R&D spending
QSAR modeling and feature analysis contribute to research innovation in drug discovery and computational chemistry.
- Moderate confidence
- The alignment is plausible and defensible but rests on an assumption a reasonable reviewer could decline. Published, and surfaced in the review queue for a human to confirm or override.
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
Viksit Bharat @2047
vb-1.2 Health and well-being
Antimicrobial research against drug-resistant pathogens directly supports infectious disease control and patient health outcomes.
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
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- Source rows resolved into this record
- 1
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Citing this record
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KIIT Deemed to be University. “A Machine Learning-Driven Approach to Identify Phytochemical Inhibitors of the Pseudomonas aeruginosa Quorum Sensing Regulator LasR”. Kortex.