cs.AI · cs.CL · cs.LG · cs.CV · cs.CR · cs.SE · stat.ML · q-fin.TR · q-fin.ST · econ.GN · q-bio.QM · physics.soc-ph · math.OC · cs.RO · cs.HC
Azim Dehghani Amirabad, Ali Khodabandeh Yalabadi, Artem Moskalev, Yun-Ching Chen, Mehdi Pirooznia and others · 2026-10-20
Cellular states are shaped by both intrinsic gene expression programs and the spatial microenvironment in which cells reside. Spatial transcriptomics makes this context measurable, but effective representation learning requires capturing both spatially informative molecular signa…
Santino Nanini, Arnaud Wiedemann, Yassir Mamouni, Cyril Schweitzer, Philippe Jouvet and others · 2026-10-20
Pulse is an actively maintained open-source adult-physiology simulator, yet its maintainers report no formal sensitivity analysis of its operational inputs. We present the first open reliability atlas across its critical-care envelope: Morris elementary-effects sampling of seven …
Haenara Shin, Dongjoo Lee, Sungwoo Bae, Kwon Joong Na, Daeseung Lee and others · 2026-10-20
VGL-stGen is a multimodal large language model adapted from a pretrained medical vision-language model using paired lung H&E and spatial transcriptomics with single-cell references. Training integrates image-expression and expression-cell-type pairs, and gene-conditioned pseu…
Lin Ha, Chen Zhou, Haozheng Luo, Han Liu, Xiaoyu Zhang and others · 2026-10-19
We propose EMBER, a structure-based framework for TCR--pMHC binding prediction that eliminates the need for a predicted docked complex, and with it the placement error that dominates such predictions. Traditional structure-based predictors utilize the co-folded complex structure …
Jamie J. Alnasir · 2026-10-19
Background: Experimental metadata are essential for interpreting archived sequencing data. In 2015, Alnasir and Shanahan examined the annotation of fragmentation, adapter ligation and enrichment in the Sequence Read Archive (SRA). This study revisits those measurements using the …
Yuji Zhao, Boris Gutman · 2026-10-19
As two most prevalent neurodegenerative diseases (NDDs), Alzheimer's disease (AD) and Parkinson's disease (PD) shared commonalities both in symptomology and pathophysiology. However, to what extent and in what way these two distinct disorders overlap remain underexplored. In this…
Wenhao Zhang, Zhongliang Zhou, Yi Ping, Zirui Wang, Sheng Li · 2026-10-19
Vision--language models (VLMs) promise to make computational pathology queryable and able to draft reports, but how much language adds beyond the vision backbone is unclear, because almost every system is evaluated by its developers on test sets of their own choosing. We grade pu…
James Kirk, Piotr Bednarski, Filip Twardy, Justin Mast, Lee von Kraus · 2026-10-19
Living plants, like animals, use electrical signals to carry information about their physiological state across their body, from roots to branches. These signals can be recorded, as they are in animals, from a pair of differential extracellular electrodes inserted into signal-con…
Xiaomeng Li · 2026-10-19
Photo-based estimation of food energy could ease dietary assessment, and general-purpose multimodal large language models (LLMs) make such estimates easy to obtain. Most evaluations use one photo taken before eating and compare with energy served, while dietary assessment needs e…
Zekai Li, Mauricio Barahona, Philipp Thomas · 2026-10-19
Uncovering stochastic reaction networks from data is central to single-cell biology. Simulation-based inference has evolved into a flexible paradigm for this purpose, circumventing the computational intractability of the likelihood. Notably, approximate Bayesian computation perfo…
Amir Khani, Christian Beste, Shervin Safavi · 2026-10-19
Spike-field couplings measure the links between neuronal spiking and local field potential (LFP) and provide a tool to study how neural populations coordinate activity across spatial and temporal scales. While modern high-density electrophysiology enables the simultaneous recordi…
Yannick Sodonougbo, Marlene Schnieders, Alexia Rizoudis, Santiago Cepeda, Frank Kramer and others · 2026-10-19
Radiomic survival studies in glioblastoma report heterogeneous prognostic features, but how much of this stems from the methodology itself is rarely examined. We analysed the association of 463 radiomic, anatomical and clinical features from pre-treatment MRI with overall surviva…
Sihan Chen, Yunlong Xu, Doruk Efe Gökmen, Michel Fruchart, Brent Doiron and others · 2026-10-18
Uncovering low-dimensional representations of brain-wide neural dynamics and their relationship to behavior remains a central challenge. Here, we show that spontaneous brain-wide rotational dynamics constrain cue-evoked behavior and learning. To systematically establish these fin…
Suxing Liu, Byungwon Min, Zhijian Zheng, Jiahao Wang · 2026-10-18
Cross-cohort evaluation of breast cancer subtype classifiers is unreliable when source and target cohorts use different annotation standards: METABRIC labels six classes, PAM50 defines five, and a claudin-low prediction cannot be correct under a five-class standard. A classifier …
Zachary Cutts, John Coller, Rachel Chen, Hua Tang, Mathias Bellaiche and others · 2026-10-17
Despite breakthroughs in AI-driven molecular generation, existing discovery pipelines operate largely in silico, with wet-lab feedback reserved for validation rather than iterative improvement. Whether large language model (LLM)-based reasoning agents can accelerate de novo disco…
Guanxing Chen, Nihui Shao, Haohuai He, Zhenchao Tang, Pengwei Hu and others · 2026-10-17
Large language models are increasingly used to guide sequential biological screens, yet standard evaluations rely on raw hit counts that conflate a proposer's value with the discovery capacity of the underlying algorithmic harness. Adaptive sampling and corrupted experimental rea…
Venkatesh Sivaraman, Joel Levin, Eric P. Mason, Victor Talisa, Suchi Saria and others · 2026-10-16
Sepsis is a major public health concern, and many sepsis patients die due to ineffective hemodynamic management. Artificial intelligence could support hemodynamic decisions, particularly in complex cases where conflicting information and comorbidities drive uncertainty and practi…
Farid Zare†, Timothy Hulshof†, Ines Thiele, Ronan M. T. Fleming · 2026-10-16
Summary: Genome-scale metabolic models increasingly challenge CPU linear-programming solvers in repeated-optimisation workflows. We present gpuGEM, an open-source Python library for GPU-based GEM optimisation using NVIDIA cuOpt, with size-adaptive settings validated against HiGHS…
Iori Azuma, Hiroyuki Kusuhara, Tadahaya Mizuno · 2026-10-16
Deep learning has achieved strong performance in computational pathology, but explaining whole-slide image (WSI) predictions remains challenging. Existing explanation methods often highlight important regions without identifying their morphological patterns, leaving a gap between…
Andy Zhang, Oscar Mickelin, Amit Singer · 2026-10-16
Single-particle cryogenic electron microscopy (cryo-EM) is an imaging technique capable of reconstructing high-resolution three-dimensional (3D) structure of biological macromolecules from a set of noisy projection images taken at random viewing directions. The mathematical model…
N. Nipu, G. Johnson, C. Roth, D. Rogers, S. R. Starkenburg and others · 2026-10-16
3D genome structures reconstructed from Hi-C data provide valuable insights into chromatin organization, but comparing them across conditions and time points remains challenging because of noise, variability, and arbitrary orientation. State-of-the-art comparison approaches often…
Priyanka Siddappa, Muntaqim Ahmed Raju, Shifat Haider Al Amin, Ruizhe Ma · 2026-10-15
Preprocessing is an under-measured reliability risk in clinical prediction: a model can keep a similar AUROC and still change who receives an alert. Imputation quality is commonly evaluated using reconstruction error or aggregate discrimination, neither of which directly measures…
Matteo Di Bernardo, Claire Peterson, Ege Topkoc, Matt Might, Iain M. Cheeseman · 2026-10-15
Optical pooled screens connect genetic perturbations to changes in cell morphology and behavior, but turning the microscopy data into interpretable results takes complex, multi-day analyses. Established pipelines process this data, yet researchers still select parameters, inspect…
Nithin Chalapathi, Theo Sternlieb, Ethan Han, Sonya M. Hanson, Pilar Cossio and others · 2026-10-15
Understanding biomolecular function requires characterizing three-dimensional structure and conformational variability, for which cryogenic electron microscopy (cryo-EM) is a powerful tool. Cryo-EM produces noisy two-dimensional particle images in which molecular structure, parti…
Joran Michiels, Anis Ismail, Maarten De Vos, Alejandro Sifrim · 2026-10-15
Existing feature attribution methods that account for feature dependencies do not scale to high dimensions. We propose causal integrated gradients (CIG) and causal expected gradients (CEG), which extend integrated gradients to incorporate prior causal structure among input featur…
Daniel Palacios, Guantong Qi, Mikael Guzman Karlsson, Shawntel K. David, Mohammed Sameeruddin and others · 2026-10-15
Objective: Trofinetide, approved in 2023 as the first Rett syndrome treatment, lacks scalable real-world monitoring because chart review is labor-intensive. We developed a dual large language model (LLM) consensus pipeline to extract 18 treatment-response phenotypes, comprising 4…
Charalampos Koilakos, Kimon-Antonios Provatas, Michail Patsakis, Candace SY Chan, Georgios A. Pavlopoulos and others · 2026-10-15
Protein foundation models increasingly support the generation of novel biological sequences, yet their reliance on large public datasets creates opportunities for adversarial manipulation of the material they learn from and retrieve. We investigate two data-only poisoning attacks…
Gideon Shaked, Siddharth Nagisetty · 2026-10-15
Computational biologists increasingly delegate substantial analyses to AI agents in long-horizon, multi-turn sessions, yet most benchmarks of agents' bioinformatics capabilities pose a single short task with a single-shot prompt. We present OmicsBench, a long-horizon, multi-turn …
Adam M. Saunders, Gaurav Rudravaram, Michael E. Kim, Elyssa M. McMaster, Yifan Shuai and others · 2026-10-14
Intro: Diffusion MRI allows for in vivo probing of brain tissue architecture via micron-level diffusion aggregated at the millimeter scale, but crossing white matter fibers decrease the sensitivity of downstream tasks such as microstructural modeling and tractography. Current fix…
Blessing Isoyiza Adeika, Onyema Osuagwu · 2026-10-14
Objective. Studies that decode imagined speech from scalp electroencephalography (EEG) commonly validate their pipelines with a positive control, usually overt speech, and report null results without stating what effect size the pipeline could have detected. Approach. Using ds003…
Nils Friederich, Philip Kohle, Maximilian Beichter, Mona Wellhäusser, Marcel Stahl and others · 2026-10-14
Promptable segmentation models turn one 3D bounding box into an instance mask. Box placement therefore limits how fast microscopy volumes with thousands of objects are annotated. Each box must be checked in several synchronized viewers, but napari-bbox shares no state between vie…
Sam Gijsen, Moritz Seiler, Kerstin Ritter · 2026-10-14
Conditional generative models are increasingly used for scientific prediction beyond the direct training support. Yet scientific questions often concern whether one intervention changes the effect of another. Such interactions can be of primary interest while explaining little of…
Kritsanavis Chongsrid, Vich Yindeedej, Supaporn Konmun, Xulei Yang, Si Yong Yeo · 2026-10-14
Catheter obstruction is the commonest cause of shunt failure; freehand insertion at Keen's point leaves the tip free in cerebrospinal fluid in only one case in ten. We built a digital twin that reconstructs skull, scalp, ear and ventricles from preoperative CT by deterministic ge…
Daniel S. Han, Vaishnavi Ananthanarayanan, Matthew J. Simpson · 2026-10-14
Fractional Brownian motion (fBM) is a model of anomalous diffusion parameterised by a Hurst exponent $H \in (0,1)$ and a generalised diffusion coefficient $D_H > 0$. We jointly estimate $H$ and $D_H$ using maximum likelihood (MLE) from density measurements with Poisson countin…
Alberto Martínez, Natalia Flechas Manrique, Llorenç Espinosa-Portalés, Luc Andrea · 2026-10-14
Large protein language models provide a powerful framework for learning sequence-function relationships and guiding experimental design. However, architectural improvements are underexplored, especially in low-compute regimes of relevance for resource-constrained research laborat…
Ashish Acharya, Aman Al Amin, Hong Qin · 2026-10-14
An agentic scientific workflow can run to completion and still release wrong results: a silent numerical error, a stale input, or a defect in a shared upstream step can contaminate several outputs while a sibling branch stays correct. We treat trust in such results as a release d…
Christian Herz, Kyle Sunderland, Matthew Daemer, Julia Iacovella, Sehdev Pressley and others · 2026-10-13
Patient-specific 3-dimensional (3D) models are increasingly central to planning surgery and catheter-based intervention in children with congenital heart disease (CHD), whose anatomy is often atypical and variable. These models inform care only when the surgeons and interventiona…
Gor Simonyan, Tatevik Abrahamyan, Narek Abelyan, Tigran Fahradyan, Hrant Khachatrian · 2026-10-13
The Practical Molecular Optimization (PMO) benchmark standardized evaluation in molecular optimization, but it is built on simple property-based oracles that do not capture structure-based drug design. As the field has moved to docking-based objectives, evaluation practice has be…
Trieu Nguyen, Frazier N. Baker, Ruoxi Gao, Daniel Adu-Ampratwum, Xia Ning · 2026-10-13
Multi-objective molecular optimization is a critical process in drug discovery that aims to modify a given molecule to simultaneously improve multiple properties while maintaining a similar overall structure. This process often requires iterative modifications guided by computati…
Jason Scheffel, Saurabh Sihag · 2026-10-13
Neuroimaging is a widely used modality for characterizing neurodegeneration in various health conditions. Brain age gap has emerged as a promising biomarker for monitoring brain health from neuroimaging data using machine learning algorithms. Recent studies have leveraged coVaria…
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