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pro vyhledávání: '"stone, eric"'
Autor:
Gall, Barnabas, Pulsford, Sacha B., Matthews, Dana, Spence, Matthew A., Kaczmarski, Joe A., Chen, John Z., Sandhu, Mahakaran, Stone, Eric, Nichols, James, Jackson, Colin J.
Protein evolution underpins life, and understanding its behavior as a system is of great importance. However, our current models of protein evolution are arguably too simplistic to allow quantitative interpretation and prediction of evolutionary traj
Externí odkaz:
http://arxiv.org/abs/2412.06115
Autor:
Li, Xuesong, Hayder, Zeeshan, Zia, Ali, Cassidy, Connor, Liu, Shiming, Stiller, Warwick, Stone, Eric, Conaty, Warren, Petersson, Lars, Rolland, Vivien
Crop biomass offers crucial insights into plant health and yield, making it essential for crop science, farming systems, and agricultural research. However, current measurement methods, which are labor-intensive, destructive, and imprecise, hinder la
Externí odkaz:
http://arxiv.org/abs/2410.23901
Autor:
Li, Xuesong, Hayder, Zeeshan, Zia, Ali, Cassidy, Connor, Liu, Shiming, Stiller, Warwick, Stone, Eric, Conaty, Warren, Petersson, Lars, Rolland, Vivien
Crop biomass, a critical indicator of plant growth, health, and productivity, is invaluable for crop breeding programs and agronomic research. However, the accurate and scalable quantification of crop biomass remains inaccessible due to limitations i
Externí odkaz:
http://arxiv.org/abs/2404.11256
Spatial transcriptomics (ST) captures gene expression within distinct regions (i.e., windows) of a tissue slide. Traditional supervised learning frameworks applied to model ST are constrained to predicting expression from slide image windows for gene
Externí odkaz:
http://arxiv.org/abs/2401.14772
This paper aims to predict gene expression from a histology slide image precisely. Such a slide image has a large resolution and sparsely distributed textures. These obstruct extracting and interpreting discriminative features from the slide image fo
Externí odkaz:
http://arxiv.org/abs/2210.16728
Spatial transcriptomics (ST) is essential for understanding diseases and developing novel treatments. It measures gene expression of each fine-grained area (i.e., different windows) in the tissue slide with low throughput. This paper proposes an Exem
Externí odkaz:
http://arxiv.org/abs/2210.16721
De novo peptide sequencing aims to recover amino acid sequences of a peptide from tandem mass spectrometry (MS) data. Existing approaches for de novo analysis enumerate MS evidence for all amino acid classes during inference. It leads to over-trimmin
Externí odkaz:
http://arxiv.org/abs/2203.13132
Publikováno v:
In Pattern Recognition January 2024 145
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