Results 171 to 180 of about 313,820 (280)

Rapid Proteome‐Wide Discovery of Protein–Protein Interactions With ppIRIS

Advanced Science, EarlyView.
ppIRIS is a lightweight deep learning framework for proteome‐wide protein–protein interaction prediction directly from sequence. By fusing evolutionary and structural embeddings with a regularized Siamese architecture, ppIRIS achieves state‐of‐the‐art accuracy across species, enables minute‐scale screening, and reveals biologically validated bacterial ...
Luiz Felipe Piochi, Di Tang, Johan Malmström, Yasaman Karami, Hamed Khakzad   +4 more
wiley   +1 more source

Assessing Genotype Imputation Methods for Low-Coverage Sequencing Data in Populations With Differing Relatedness and Inbreeding Levels. [PDF]

Mol Ecol Resour
Vi T, Stuart KC, Tan HZ, Lloret-Villas A, Santure AW.   +4 more
europepmc   +1 more source

Imputation methods for missing failure times in recurrent-event survival analysis: Application to suicide attempts in the transgender population. [PDF]

PLoS One, 2022
Liu S, Reisner SL, Herman JL, Weller E.
europepmc   +1 more source

Leveraging Artificial Intelligence and Large Language Models for Cancer Immunotherapy

Advanced Science, EarlyView.
Cancer immunotherapy faces challenges in predicting treatment responses and understanding resistance mechanisms. Artificial intelligence (AI) and machine learning (ML) offer powerful solutions for cancer immunotherapy in patient stratification, biomarker discovery, treatment strategy optimization, and foundation model development.
Xinchao Wu, Mengtao Sun, Lusheng Li, Jieqiong Wang, Shibiao Wan   +4 more
wiley   +1 more source

Prompt Engineering Accelerates the Data‐Driven Discovery of Photocatalysts via an LLM‐Based Model Ensemble Strategy

Advanced Science, EarlyView.
This work establishes a pipeline that transforms fragmented literature into a structured database for graphitic carbon nitride photocatalyst discovery. A prompt‐engineered, cross‐model large language model ensemble automates high‐fidelity extraction, enabling interpretable machine learning to identify dominant performance descriptors. These data‐driven
Dianyuan Li, Xichen Sun, Shaohua Sun, Runzhou Wang, Miaomiao Zhang, Meng Xiao, Yue Wang, Yuezhou Zhang   +7 more
wiley   +1 more source

The impact of missing data rates and imputation methods on the assumption of unidimensionality. [PDF]

PLoS One
Baniamer AO.
europepmc   +1 more source

scIMC: a platform for benchmarking comparison and visualization analysis of scRNA-seq data imputation methods. [PDF]

Nucleic Acids Res, 2022
Dai C, Jiang Y, Yin C, Su R, Zeng X, Zou Q, Nakai K, Wei L.   +7 more
europepmc   +1 more source

PAIR: Reconstructing Single‐Cell Open‐Chromatin Landscapes for Transcription Factor Regulome Mapping

Advanced Science, EarlyView.
scATAC‐seq analysis is often constrained by limited sequencing depth, extreme sparsity, and pervasive technical missingness. PAIR is a probabilistic framework that restores scATAC‐seq accessibility profiles by directly modeling the native cell–peak bipartite structure of chromatin accessibility.
Yanchi Su, Qi Qi, Yi Fan, Yubo Wang, Gaoyang Hao, Ka‐Chun Wong, Yunhe Wang, Xiangtao Li   +7 more
wiley   +1 more source

Bridging the Gap: Missing Data Imputation Methods and Their Effect on Dementia Classification Performance. [PDF]

Brain Sci
Aracri F, Bianco MG, Quattrone A, Sarica A.   +3 more
europepmc   +1 more source

Are dropout imputation methods for scRNA-seq effective for scHi-C data? [PDF]

Brief Bioinform, 2021
Han C, Xie Q, Lin S.
europepmc   +1 more source