Work

Deliverable D2.1 – Toolbox improved in silico models for identification of PMT properties

Year: 2025

Type: article

Abstract: This H2020 PROMISCES deliverable presents an enhanced toolbox of in silico models designed to identify PMT (Persistent, Mobile, and Toxic) properties of chemical substances.

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.14800914

Authors: Sosnowska, Anita, Puzyn, Tomasz, peijnenburg, willie, Wassenaar, Pim

Institutions: University of Gdańsk, Leiden University, University of Amsterdam, National Institute for Public Health and the Environment

Language: English

Topic: Computational Drug Discovery Methods

Subfield: Computational Theory and Mathematics

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

Funder: European Commission

Award: Preventing Recalcitrant Organic Mobile Industrial chemicalS for Circular Economy in the Soil-sediment-water system

OpenAlex ID: W6893167902

FWCI:

Cites:

Cited by:

Related to: