Results 241 to 250 of about 93,106 (305)

BEERS2: RNA-Seq simulation through high fidelity in silico modeling. [PDF]

Brief Bioinform
Brooks TG, Lahens NF, Mrčela A, Sarantopoulou D, Nayak S, Naik A, Sengupta S, Choi PS, Grant GR.   +8 more
europepmc   +1 more source

Autonomous AI‐Driven Design for Skin Product Formulations

Advanced Intelligent Discovery, EarlyView.
This review presents a comprehensive closed‐loop framework for autonomous skin product formulation design. By integrating artificial intelligence‐driven experiment selection with automated multi‐tiered assays, the approach shifts development from trial‐and‐error to intelligent optimisation.
Yu Zhang, Yongrui Xiao, Chunlin Chen, Dimitrios Tsaoulidis, Kai Yang, Tao Chen   +5 more
wiley   +1 more source

MSC-extracellular vesicle microRNAs target host cell-entry receptors in COVID-19: in silico modeling for in vivo validation. [PDF]

Stem Cell Res Ther
Al Saihati HA, Dessouky AA, Salim RF, Elgohary I, El-Sherbiny M, Ali FEM, Moustafa MMA, Shaheen D, Forsyth NR, Badr OA, Ebrahim N.   +10 more
europepmc   +1 more source

When Biology Meets Medicine: A Perspective on Foundation Models

Advanced Intelligent Discovery, EarlyView.
Artificial intelligence, and foundation models in particular, are transforming life sciences and medicine. This perspective reviews biological and medical foundation models across scales, highlighting key challenges in data availability, model evaluation, and architectural design.
Kunying Niu, Yuxing Wang, Limin Zou, Jing Huang   +3 more
wiley   +1 more source

Author Correction: Multi-target in-silico modeling strategies to discover novel angiotensin converting enzyme and neprilysin dual inhibitors. [PDF]

Sci Rep
Shah SK, Chaple DR, Masand VH, Jawarkar RD, Chaudhari S, Abiramasundari A, Zaki MEA, Al-Hussain SA.   +7 more
europepmc   +1 more source

AI‐Driven Cancer Multi‐Omics: A Review From the Data Pipeline Perspective

Advanced Intelligent Discovery, EarlyView.
The exponential growth of cancer multi‐omics data brings opportunities and challenges for precision oncology. This review systematically examines AI's role in addressing these challenges, covering generative models, integration architectures, Explainable AI for clinical trust, clinical applications, and key directions for clinical translation.
Shilong Liu, Shunxiang Li, Kun Qian
wiley   +1 more source

An in-silico modeling approach to separate exogenous and endogenous plasma insulin appearance, with application to inhaled insulin. [PDF]

Sci Rep
Piersanti A, Pacini G, Tura A, D'Argenio DZ, Morettini M.   +4 more
europepmc   +1 more source

AS‐pHopt: An Optimal pH Prediction Model Enhanced by Active Site of Enzymes

Advanced Intelligent Discovery, EarlyView.
To address the low accuracy of enzyme optimal pH (pHopt) prediction, this study develops active site‐based pHopt (AS‐pHopt), a prediction model enhanced by active site information and pseudo‐label prediction. Integrating key structural and physicochemical features affecting enzyme pHopt, AS‐pHopt uses Evolutionary Scale Modeling (ESM)‐2 with active ...
Wenxiang Song, Xinmin Li, Hongbo Yu, Le Xiong, Guixia Liu, Weihua Li, Yun Tang   +6 more
wiley   +1 more source

In silico modeling and simulation of organ-on-a-chip systems to support data analysis and a priori experimental design. [PDF]

CPT Pharmacometrics Syst Pharmacol
Milani N, Parrott N, Galetin A, Fowler S, Gertz M.   +4 more
europepmc   +1 more source

Accelerating Discovery of Organic Molecular Crystals via Materials Informatics and Autonomous Experiments

Advanced Intelligent Discovery, EarlyView.
Materials informatics and autonomous experimentation are transforming the discovery of organic molecular crystals. This review presents an integrated molecule–crystal–function–optimization workflow combining machine learning, crystal structure prediction, and Bayesian optimization with robotic platforms.
Takuya Taniguchi, Kazuki Ishizaki, Ryo Fukasawa   +2 more
wiley   +1 more source