bioRxiv

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Localized Space Coding and Phase Coding Complement Each Other to Achieve Robust and Efficient Spatial Representation

bioRxiv Jan 1, 2025
Localized space coding and phase coding are two distinct strategies responsible, respectively, for representing abstract structure and sensory observations in neural cognitive maps. In spatial representation, localized space coding is implemented by ...
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A neural model for V1 that incorporates dendritic nonlinearities and back-propagating action potentials

bioRxiv Jan 1, 2025
The work of Hubel and Wiesel has been instrumental in shaping our understanding of V1, leading to modeling neural responses as cascades of linear and nonlinear processes in what is known as the “standard model” of vision. Under this formulation, howe...
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PATTY corrects open chromatin bias for improved bulk and single-cell CUT&Tag profiling

bioRxiv Jan 1, 2025
Precise profiling of epigenomes is essential for better understanding chromatin biology and gene regulation. Cleavage Under Targets & Tagmentation (CUT&Tag) is an efficient epigenomic profiling technique that can be performed on a low number of cells...
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Evaluating BOLD functional MRI biophysical simulation approaches: impact of vascular geometry, magnetic field calculations, and water diffusion models

bioRxiv Jan 1, 2025
Biophysical simulations have guided the development of blood oxygenation level-dependent (BOLD) functional MRI (fMRI) acquisitions and signal models that relate the BOLD signal to the underlying physiology, such as calibrated BOLD and vascular finger...
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Advanced Deep Learning Enables Prediction of Allogeneic Stem Cell Mobilization Success

bioRxiv Jan 1, 2025
Hematopoietic stem and progenitor cell (HSPC) transplantation offers a potentially curative therapy for aggressive hematologic malignancies and bone marrow failure syndromes. Successful transplantation depends on effective mobilization of donor CD34+...
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An Improved Dataset for Predicting Mammal Infecting Viruses from Genetic Sequence Information

bioRxiv Jan 1, 2025
There have been several attempts to develop machine learning (ML) models to identify human infecting viruses from their genomic sequences, with varying degrees of success. Direct comparison between models is problematic, because these models are typi...
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Reconstructing the Mitochondrial Proton Motive Force Using Physics-Informed Neural Networks and Surrogate Bioenergetic Signals

bioRxiv Jan 1, 2025
The mitochondrial proton motive force (PMF) underlies ATP synthesis, metabolite transport, and energy coupling. Yet, direct measurement of PMF remains technically challenging due to probe invasiveness, calibration drift, and compartmental averaging. ...
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Encoding neural representations of time-continuous stimulus-response transformations in the human brain with advanced deep neural networks

bioRxiv Jan 1, 2025
Human behavior arises from the continuous transformation of sensory input into goal-directed actions. While existing analytical methods often break time into discrete events, the stages and underlying representations involved in stimulus-response (S-...
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A Generative Foundation Model for Antibody Design

bioRxiv Jan 1, 2025
Antibodies are indispensable components of the immune system, yet the design of high-affinity antibodies remains a time-consuming and experimentally intensive process. To address this challenge, we present IgGM, a novel generative foundation model de...
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Modeling the Biomechanical Features Affecting the Metabolic Rate of Walking with a Powered Ankle-Foot Prosthesis

bioRxiv Jan 1, 2025
For individuals with unilateral transtibial amputation, powered ankle-foot prostheses have the potential to reduce the metabolic rate of walking, which could contribute to improvements in mobility and quality of life; however, physiological improveme...
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