Search · four archives
Search · four archives
12 papers · ranked by Valyu relevance
Yiming Xue, Xiaojian Liu, Weimin Zhu, Shengfan Wang + 2 more
While protein-RNA interactions are fundamental to post-transcriptional processes, achieving a holistic understanding of their regulatory logic remains challenging. Current computational models often treat binding affinity, interface mapping, and RNA design as isolated tasks, thereby failing to provide a unified…
Zichao Jin, Jiaoru Wang, Wenjiang Huang, Jingcheng Zhang + 2 more
Accurate, reliable, large-scale disease predictions are essential to ensure rice production. Existing disease prediction models often face a trade-off between interpretability and predictive capability, necessitating the integration of mechanistic knowledge and data-driven learning within a modelling framework.…
Pao‐Yuan Huang, Heng‐Syu Lin, Cheng‐Yuan Peng, Ruei‐Hau Hsu + 1 more
Few prediction models have been specifically designed to evaluate the risk of hepatocellular carcinoma (HCC) in patients with chronic hepatitis B and cirrhosis. This study aimed to develop a machine learning-based prediction model to assess the risk of developing HCC in patients with hepatitis B virus (HBV)-related…
Niyazi Samet Yilmaz, Bayram Sen, Sena Turkmen, Hikmet Can Çubukçu + 1 more
Title: Graphical abstract
Paul B. Conn, Irina S. Trukhanova, Peter L. Boveng, Vladimir Chernook + 1 more
In the springs of 2012-2013, Russian Federation scientists conducted aerial surveys of ice-associated seals (including bearded, ribbon, ringed, and spotted seals) in the Sea of Okhotsk and in Russian waters of the western Bering Sea. These instrument-based surveys used a combination of thermal imaging and digital…
Amrita Nagasuri, Umair Khan, Parker Grosjean, Adi Siddharth + 15 more
Endometriosis is a chronic inflammatory disease associated with pelvic pain, infertility, and delayed diagnosis. Growing evidence suggests that altered DNA methylation contributes to disease development and could serve as a biomarker for disease. We developed a leakage-safe machine learning pipeline to classify…
Danny Vu, Andrew Kowalczewski, Sarah D. Burnett, Courtney Sakolish + 4 more
Cardiotoxicity remains a major cause of drug attrition and postmarket withdrawal, yet the vast majority of environmental chemicals to which humans may be exposed remain uncharacterized for cardiotoxicity risk. Human induced pluripotent stem cell (hiPSC)-based testing has been proposed to address this gap. Here, we…
Eliezer Masliah
How transient neural representations become integrated and stable enough to function as internal neural models remains incompletely understood. Grounded in efficient coding, Bayesian and predictive frameworks, recurrent and attractor dynamics, neural state-space models, and systems neuroscience, the Principle of…
Bach Tran Nguyen, Aurélie Barrail-Tran, Moreno Ursino, Sébastien Goutal + 6 more
First-in-human studies require dose extrapolation from pharmacokinetic animal studies combined with safety assessments. Subtherapeutic doses of radiolabelled drugs can be administered in preclinical and early clinical development to gain a dynamic pharmacokinetic understanding, potentially informing…
Daniel L Riddle, Levent Dumenci
Sir-, Rajamäki and colleagues were interested in identifying preoperative predictors of persistent pain 1-year post-surgery in patients undergoing knee arthroplasty [1]. Given the clinical importance of persistent pain following this typically highly successful surgery, prognostic studies of poor pain outcome are…
Yilan Wu, Dun Jack Fu, Yukun Zhou, Siegfried K Wagner + 2 more
Background Large language model (LLM) agents capable of generating and executing statistical code from natural language may broaden access to clinical data analysis, yet which pipeline stages they perform reliably and which require expert oversight remain poorly defined. Objective This study aimed to evaluate the…
Linsui Deng, Kejun He, Xianyang Zhang
Mendelian randomization (MR) has been widely used to infer causal relationships between exposures and outcomes in epidemiological studies. However, classical MR assumptions can be violated when genetic variants are associated with outcomes through pathways other than the exposure, leading to uncorrelated and/or…