AIMC Journal:
bioRxiv

Showing 3071 to 3080 of 4993 articles

A scalable computational framework for predicting gene expression from candidate cis-regulatory elements

bioRxiv Jan 1, 2025
Deciphering the relationships between cis-regulatory elements (CREs) and target gene expression has been a long-standing unsolved problem in molecular biology, and the dynamics of CREs in different cell types make this problem more challenging. To ad...
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Tonotopically distinct OFF responses arise in the mouse auditory midbrain following sideband suppression

bioRxiv Jan 1, 2025
The parsing of sensory information into discrete topographic domains is a fundamental principle of sensory processing. In the auditory cortex, these domains evolve during a stimulus, with the onset and offset of tones evoking distinct spatial pattern...
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STORIES: learning cell fate landscapes from spatial transcriptomics

bioRxiv Jan 1, 2025
In dynamic biological processes such as development, spatial transcriptomics is revolutionizing the study of the mechanisms underlying spatial organization within tissues. Inferring cell fate trajectories from spatial transcriptomics profiled at seve...
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Allostery is a widespread cause of loss-of-function variant pathogenicity

bioRxiv Jan 1, 2025
Allosteric communication between non-contacting sites in proteins plays a fundamental role in biological regulation and drug action. While allosteric gain-of-function variants are known drivers of oncogene activation, the broader importance of allost...
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Uncertainty in Deep Learning for EEG under Dataset Shifts

bioRxiv Jan 1, 2025
As artificial intelligence (AI) is increasingly integrated into medical diagnostics, it is essential that predictive models provide not only accurate outputs but also reliable estimates of uncertainty. In clinical applications, where decisions have s...
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Closing the loop: Teaching single-cell foundation models to learn from perturbations

bioRxiv Jan 1, 2025
The application of transfer learning models to large scale single-cell datasets has enabled the development of single-cell foundation models (scFMs) that can predict cellular responses to perturbations in silico. Although these predictions can be exp...
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Situation Models in the Brain are Used to Resolve Word References

bioRxiv Jan 1, 2025
Resolving the meaning of a pronoun requires retrieving information about a unique individual (a referent) from many remembered experiences and inferences throughout sensory and cognitive modalities, from vision and audition to episodic memory and soc...
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scHDeepInsight: A Hierarchical Deep Learning Framework for Precise Immune Cell Annotation in Single-Cell RNA-seq Data

bioRxiv Jan 1, 2025
Immune cell classification from single-cell RNA sequencing (scRNA-seq) presents significant challenges due to complex hierarchical relationships among cell types. We introduce scHDeepInsight, a deep learning framework that extends our previous scDeep...
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ProtLoc-GRPO: Cell line-specific subcellular localization prediction using a graph-based model and reinforcement learning

bioRxiv Jan 1, 2025
Subcellular localization prediction is crucial for understanding protein functions and cellular processes. Subcellular localization is dependent on tissue and cell lines derived from different cell types. Predicting cell line-specific subcellular loc...
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Cortical neural landscape captures mouse-to-mouse variability in anticipatory vs. inattentive decision making

bioRxiv Jan 1, 2025
Understanding individual variability in behavior is crucial for both basic and clinical neuroscience, yet it remains challenging to study in traditional single laboratory experiments with small sample size. Leveraging standardized behavioral and neur...
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