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For decades, scientists believed that associative learning – understanding that two events are linked to each other, like a stimulus and a response – required at least some form of...
The collaboration brings together OneCyte's proprietary single-cell platform for high-throughput and high-speed clone selection with Kemp Proteins' molecular engineering capabiliti...
Brainless but brilliant: New study reveals how a giant single-celled organism uses neuron-like molecular machinery to learn and remember.
RNA sequencing combined with deep learning improves identification of cell populations and key genes, enabling more accurate analysis of complex single cell datasets...
A collaborative research group has shown that biological neurons can be trained to perform a temporal pattern learning task that was previously carried out by artificial systems.
by Yixiang Huang, Yuan Gan, Xinqi Gong Multi-omics profiling—spanning proteomics, transcriptomics, and additional omics data types—is rapidly advancing, providing increasingly det...
In a preprint published in arXiv, researchers from Altos Labs have described a machine learning algorithm that performs end-to-end prediction of how cells’ gene expression will res...
Researchers have successfully trained living biological neurons to perform complex machine learning tasks. By using microfluidic devices and "FORCE learning," the team demonstrated...
RNA sequencing analysis with scDecorr improves integration of single-cell datasets by reducing noise and preserving biological signals, enabling more accurate clustering and...
PhytoCell uses machine learning with RNA sequencing to identify marker genes and classify plant cell subpopulations, improving accuracy in complex single-cell datasets...
by Yilang Li, Yidi Sun, Aoyun Geng, Junlin Xu, Yajie Meng, Feifei Cui, Leyi Wei, Quan Zou, Xiulai Li, Zilong Zhang Cell type annotation in single-cell RNA sequencing is a critical...
by Zhipeng Zhou, Yang Zhang, Zhiming Dai Rapid advancements in technology enables the measurement of multimodal data at single-cell resolution, but with emerging modalities that a...
by Sami Mollard, Sander M. Bohte, Pieter R. Roelfsema Natural scenes usually contain many objects that need to be segregated from each other and the background. Object-based atten...
by Dongning Liu, Muzhi Wang, Huan Luo Ranking—a ubiquitous relational structure—enables humans to organize complex information and overcome cognitive load, yet in real-world setti...
Scientists have pinpointed a single synaptic connection in the basal ganglia as the origin point for vocal learning. By studying zebra finches, researchers discovered that "turning...
RNA sequencing from more than 22 million cells trained a model that predicts cell-type-specific gene expression and noncoding variant...
What if an unsupervised model could become a strong classifier with only a handful of labels? The post You Don’t Need Many Labels to Learn appeared first on Towards Data Science.
by Jiasong Li, Lingwei Tang, Xinhang Wei, Yumin Chen, Haibing Xu Flexible goal‑directed navigation requires integrating changing goal information with a stable spatial map, yet ho...
So I was reading about this study the other night (as one does 🫠), the one where researchers mapped every single neuron of a fruit fly…Continue reading on Medium »
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