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Life Sciences
Life scientists post their preprints on bioRxiv, and quantitative biology appears on arXiv too. This page shows the newest papers ReadSearch has read from both, from cell biology and genetics to neuroscience, ecology and immunology.
709 papers, from 31 August 2026 to 6 November 2026: 426 arXiv preprints, 228 bioRxiv preprints and 55 OpenAlex records.
Newest papers, page 32
Optical microelectrode arrays for differential readout of electrical and mechanical signals in cardiac cells
Simultaneous assessment of electrical excitation and mechanical contraction is essential for understanding cardiac cell function, yet these two processes are commonly measured with separate…A neural-astrocyte architecture implements a hybrid automaton for evidence accumulation
Astrocytes are non-neuronal glial cells that are receiving widespread attention due to their emerging role in neural computation.Democratizing Clinical Tumor Whole Genome Sequencing: 18-hour End-to-end Analysis via Trillion-parameter Large Language Models Locally Deployed on Consumer-grade Hardware
Whole genome sequencing (WGS) is essential for precision oncology, yet its clinical adoption remains limited by prohibitive computational costs and multi-day turnaround times.An immune world model for multiscale forecasting and therapeutic hypothesis generation
Immune therapies act across cell-intrinsic programs, tissue ecosystems, and patient-specific immune states, yet most predictors address these scales separately.Structure is not mechanism: high-gain gated-FFN rows across text and genomic foundation models
A small number of unusually high-gain parameters can exert disproportionate effects in transformer language models, but whether analogous structures recur in genomic foundation models and whether…Nonlinear dynamics of random neural networks with second-order synaptic motifs
Classical theories of random neural networks typically assume independent connectivity, overlooking the local motif structures prevalent in biological circuits.URCHIN: A Horizontal Spiking Language Model for Data-Constrained Pretraining
The BabyLM challenge measures how much language a model can learn from developmentally-plausible, child-scale data rather than internet-scale corpora, yet prior language models forgo the biological…Same Encoder, Different Winner: A Paired-View Framework for Cell Painting Encoder Evaluation
Vision encoders for Cell Painting are typically ranked by a single evaluation, commonly replicate mean average precision (mAP).NOC NOC, who's there? Clustering systems of tree-child and normal networks
Clustering systems provide a natural way to encode structural information contained in phylogenetic networks.LabAgent: Customize Any Research Hubs for Scientific Discoveries Using AI Agents
Scientific research is a continuous process that emphasizes inheritance.Pretraining for Sample-Efficient Neural Interfaces
Brain-computer interfaces (BCIs) decode neural activity to restore lost function.The Platonic brain bridge hypothesis: human brain networks as an architectural prior for multimodal large language models
Multimodal large language models predict brain activity, but brain alignment has been a measurement, not a design tool.Biology-in-the-loop: Amortized Adaptive Hit Discovery in CRISPR Screens
Many biological discovery problems require experiments to be selected sequentially under constrained budgets.Predicting Collision Cross Sections with GRACE: Geometric Residual Adduct Conditioning via Early-fusion
Collision cross section (CCS), derived from ion mobility mass spectrometry, is a common descriptor for molecular annotation.HypoKG: Evidence-Disciplined Biomedical Hypothesis Generation Beyond Endpoint Knowledge
Large language models (LLMs) can generate biomedical hypotheses, but it remains unclear whether they truly reason from scientific evidence or simply produce convincing-sounding ideas.EEGBind: Detecting Source-Level Interictal Epileptiform Discharges via EEG-Centric Multimodal Binding
Source-level analysis of interictal epileptiform discharges (IEDs) is relevant to presurgical evaluation and treatment planning because it helps characterize where epileptiform activity is likely to…ProMeta: Few-shot PROTAC-targeted degradation prediction across E3 ligases
Proteolysis-targeting chimeras (PROTACs) have emerged as a transformative therapeutic strategy that selectively degrades historically ''undruggable'' targets via the ubiquitin-proteasome system.A Bio-Plausible Visual Neural Network for Locust-Inspired Collision Perception
Locust visual systems have long served as an important biological paradigm for studying looming perception and collision avoidance.Are You Learning Biological Signal or Shortcuts? Auditing and Mitigating Bias in Protein-Protein Interaction Datasets
Protein-protein interaction (PPI) databases do not faithfully reflect biological realities.BrainTaskonomy: Learning How to Pretrain and What to Transfer in fMRI Foundation Models
fMRI foundation models increasingly aggregate heterogeneous data across brain states, cohorts, and acquisition settings, yet pretraining domains are commonly treated as a flat mixture and downstream…
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