Patrick CN Martin, PhD

Patrick CN Martin, PhD

Research Data Scientist - Bioinformatician - Data Manager - Molecular Biologist - Writer

Publications

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Journal Articles

Ovarian tumor cells gain competitive advantage by actively reducing the cellular fitness of microenvironment cells

Published in Nature Biotechnology, 2024

Here we demonstrate that the expression of Flower Lose and reduced microenvironment fitness is not a pre-existing condition but, rather, a cancer-induced phenomenon

Recommended citation: Madan, E., Palma, A.M., Vudatha, V. et al. Ovarian tumor cells gain competitive advantage by actively reducing the cellular fitness of microenvironment cells. Nat Biotechnol (2024). https://doi.org/10.1038/s41587-024-02453-3
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Integrating Prior Knowledge Using Transformer for Gene Regulatory Network Inference

Published in Advanced Science, 2024

By combining LLMs ability to distillate biological knowledge from text and deep learning methodologies capturing complex patterns in gene expression data, GRNPT overcomes the limitations of traditional GRN inference methods and enables more accurate and comprehensive understanding of gene regulatory dynamics.

Recommended citation: G. Weng, P. Martin, H. Kim, K. J. Won, Integrating Prior Knowledge Using Transformer for Gene Regulatory Network Inference. Adv. Sci. 2024, 2409990. https://doi.org/10.1002/advs.202409990
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Multi-scale and multi-context interpretable mapping of cell states across heterogenous spatial samples.

Published in biorxiv, 2024

There is a growing demand for methods that can effectively align and compare spatial data in the absence of obvious visual correspondence. To address this challenge, we developed an interpretable cell mapping strategy by considering spatial context at various scales.

Recommended citation: Multi-scale and multi-context interpretable mapping of cell states across heterogenous spatial samples Patrick C.N. Martin, Wenqi Wang, Hyobin Kim, Henrietta Holze, Kyoung Jae Won bioRxiv 2024.08.31.610638; doi: https://doi.org/10.1101/2024.08.31.61063
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ChatGPT and large language models in academia: opportunities and challenges

Published in BioData Mining, 2023

In this editorial, we discuss this technology from the academic’s perspective with regard to its limitations and utility for academic writing, education, and programming

Recommended citation: Meyer, J.G., Urbanowicz, R.J., Martin, P.C.N. et al. ChatGPT and large language models in academia: opportunities and challenges. BioData Mining 16, 20 (2023). https://doi.org/10.1186/s13040-023-00339-9
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