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Open Access research that better understands changing marine ecologies...

Strathprints makes available scholarly Open Access content by researchers in the Department of Mathematics & Statistics.

Mathematics & Statistics hosts the Marine Population Modelling group which is engaged in research into topics surrounding marine resource modelling and ecology. Recent work has included important developments in the population modelling of marine species.

Explore the Open Access research of Mathematics & Statistics. Or explore all of Strathclyde's Open Access research...

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Number of items: 7.


Mason, Joseph and Wilders, Harry and Fallon, David J. and Thomas, Ross P. and Bush, Jacob T. and Tomkinson, Nicholas C. O. and Rianjongdee, Francesco (2023) Automated LC-MS analysis and data extraction for high-throughput chemistry. Digital Discovery, 2 (6). pp. 1894-1899. ISSN 2635-098X

Bugeja, Nathalie and Oliver, Cameron and McGrath, Nicole and McGuire, Jake and Yan, Chunhui and Carlysle-Davies, Felicity and Reid, Marc (2023) Teaching old presumptive tests new digital tricks with computer vision for forensic applications. Digital Discovery, 2 (4). pp. 1143-1151. ISSN 2635-098X

Pereira Diaz, Laura and Brown, Cameron J. and Ojo, Ebenezer and Mustoe, Chantal and Florence, Alastair J. (2023) Machine learning approaches to the prediction of powder flow behaviour of pharmaceutical materials from physical properties. Digital Discovery, 2 (3). pp. 692-701. ISSN 2635-098X

Vassileiou, Antony D. and Robertson, Murray N. and Wareham, Bruce G. and Soundaranathan, Mithushan and Ottoboni, Sara and Florence, Alastair J. and Hartwig, Thoralf and Johnston, Blair F. (2023) A unified ML framework for solubility prediction across organic solvents. Digital Discovery, 2 (2). pp. 356-367. ISSN 2635-098X

Wilkinson, Matthew R. and Pereira Diaz, Laura and Vassileiou, Antony D. and Armstrong, John A. and Brown, Cameron J. and Castro-Dominguez, Bernardo and Florence, Alastair J. (2023) Predicting pharmaceutical powder flow from microscopy images using deep learning. Digital Discovery, 2 (2). pp. 459-470. ISSN 2635-098X

Fowles, Daniel J. and McHardy, Rose G. and Ahmad, Abdullah and Palmer, David S. (2023) Accurately predicting solvation free energy in aqueous and organic solvents beyond 298 K by combining deep learning and the 1D reference interaction site model. Digital Discovery, 2 (1). pp. 177-188. ISSN 2635-098X

Maldonado, Diego A. and Vassileiou, Antony and Johnston, Blair and Florence, Alastair J. and Brown, Cameron J. (2022) Data mining crystallization kinetics. Digital Discovery, 1 (5). pp. 621-635. ISSN 2635-098X

This list was generated on Sat Jun 15 02:21:30 2024 BST.