bioRxiv

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Stable Maintenance of Two-Cell-Like Cells from Embryonic Stem Cells Reveals Chromatin and Super Enhancer Regulation of MERVL Elements

bioRxiv
Mouse embryonic stem cells (ESCs) occasionally transit into a rare two-cell-like (2C) state characterized by transient activation of endogenous retroviruses such as MERVL and expression of 2C-specific genes including the Zscan4 cluster. These 2C-like...

Predicting Risk of Transfusion-Induced Red Blood Cell Alloimmunization Using Statistical and Machine Learning Approaches in the Recipient Epidemiology and Donor Evaluation Study (REDS-III) Database

bioRxiv
Red blood cell (RBC) alloimmunization is a common complication from blood transfusion, often resulting in accelerated donor RBC destruction. Patients show substantial variation in their predisposition to RBC alloimmunization. Previous studies have id...

PTF-Vāc: An explainable and generative deep co-learning encoders-decoders system for ab-initio discovery of plant transcription factor binding sites

bioRxiv
Discovery of transcription factors (TFs) binding sites (TFBS) and their motifs in plants pose significant challenges due to high cross-species variability. The interaction between TFs and their binding sites is highly specific and context dependent. ...

Towards an AI-based knowledge assistant for goat farmers based on Retrieval-Augmented Generation

bioRxiv
Large language models (LLMs) are increasingly being recognised as valuable knowledge communication tools in many industries. However, their application in livestock farming remains limited, being constrained by several factors not least the availabil...

STRUMP-I: Structure-based machine learning approach to pMHC-I binding prediction using force field energy features

bioRxiv
The adaptive immune system monitors cellular integrity by recognizing short peptides from intracellular proteins presented on Major Histocompatibility Complex class I (MHC-I) molecules, collectively termed peptide-MHC complexes (pMHC), enabling detec...

Deep Learning Detection and Classification of Red Blood Cells: Towards a Universal Dataset

bioRxiv
We evaluate emerging machine learning models for pattern recognition, focusing on the YOLOv11 architecture for detecting and classifying red blood cell shapes. Our analysis targets two characteristic morphologies observed under flow: slipper and para...

scPortrait integrates single-cell images into multimodal modeling

bioRxiv
Machine learning increasingly uncovers rules of biology directly from data, enabled by large, standardized datasets. Microscopy images provide rich information on cellular architecture and are accessible at scale across biological systems, making the...

LoFT-TCR: A LoRA-based Fine-tuning Framework for TCR-Antigen Binding Prediction

bioRxiv
T cells recognize and eliminate diseased cells by binding their T cell receptors (TCRs) to short endogenous peptides (antigens) presented on the cell surface. Such interactions are central to adaptive immunity, yet current experimental approaches to ...

CASTLE: a training-free foundation-model pipeline for cross-species behavioral classification

bioRxiv
Accurately and efficiently quantifying animal behavior at scale without intensive manual labeling is a long-standing challenge for neuroscience and ethology. Keypoint-based tracking emphasizes simplicity and efficiency but loses the richness of postu...

Single-cell proteomics of pancreatic islet cells reveals type 1 diabetes and donor-specific features

bioRxiv
Type 1 diabetes mellitus (T1DM) is the most common severe chronic disease in children and adolescents and requires life-long exogenous insulin treatment. Investigating key differences between the pancreas of healthy and T1DM patients is key to help u...