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Pages

Posts

publications

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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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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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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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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software

lighteR

Published:

Analysis of plant photosynthetic efficiency data.

ChIPanalyser

Published:

ChIPanalyser: Predicting Transcription Factor Binding Sites

Kuresi

Published:

Cancer Competition R package and python module.

Vesalius

Published:

Vesalius: Dissecting Tissue Anatomy from Spatial Transcriptomic Data

talks

teaching

Teaching experience 1

Undergraduate course, University 1, Department, 2014

This is a description of a teaching experience. You can use markdown like any other post.

writing