Results 121 to 130 of about 12,301 (257)

APOE‐stratified Proteomic and Metabolomic Analysis Reveals Mitochondrial Dysfunction Inflammation and Lipid Dysregulation in Alzheimer's Disease

Advanced Science, EarlyView.
A large‐scale multiomic dataset (proteomic and metabolomic) comprising 3,060 plasma samples were analyzed to identify proteins, metabolites, pathways, and protein‐associated drugs linked to Alzheimer’s Disease (AD) independently of apolipoprotein E (APOE). AD was associated with a distinct molecular signature that captures.
Fuhai Li, Yike Chen, Daniel Western, Muhammad Ali, Menghan Liu, Katherine Gong, Ying Xu, Joseph Lowery, David M. Holtzman, Chloe Robins, John D. Eicher, Yen‐Ning Huang, ShiWei Liu, Tamina Park, Andrew J. Saykin, Kwangsik Nho, Mahdi Moqri, Richard C. Mohs, Amelia Farinas, Patricia Moran‐Losada, Hamilton Se‐Hwee Oh, Tony Wyss‐Coray, Carlos Cruchaga   +22 more
wiley   +1 more source

Identification and Characterization of an In Silico Designed Membrane‐Active Peptide with Antiviral Properties

Advanced Science, EarlyView.
An evolutionary molecular dynamics platform is used to design P1.6, a membrane‐active peptide that senses lipid packing defects in viral envelopes. P1.6 adopts a stabilized α‐helical structure upon membrane contact, disrupts virus‐like liposomes, and damages HIV‐1 particles.
Pascal von Maltitz, Niek van Hilten, Tatjana Weil, Thunchanok Thummaraj, Jeroen Methorst, Dennis Aschmann, Alexander Kros, Clarissa Read, Jasmina Gačanin, Herre Jelger Risselada, Jan Münch   +10 more
wiley   +1 more source

SiCmiR Atlas: Single‐Cell miRNA Landscape Reveals Hub‐miRNA and Network Signatures in Human Cancers

Advanced Science, EarlyView.
SiCmiR predicts mature miRNA activity at single‐cell resolution using only 977 landmark genes, enabling scalable reconstruction of miRNA landscapes across diverse tissues and disease contexts. The SiCmiR Atlas integrates 9.36 million cells with analytical tools for hub‐miRNA discovery, biomarker prioritization, and regulatory network interrogation ...
Xiao‐Xuan Cai, Jing‐Shan Liao, Jia‐Jun Ma, Yu‐Xuan Pang, Yi‐Gang Chen, Yang‐Chi‐Dung Lin, Yi‐Dan Chen, Xin Cao, Yi‐Cheng Zhang, Tao‐Sheng Xu, Tzong‐Yi Lee, Hsi‐Yuan Huang, Hsien‐Da Huang   +12 more
wiley   +1 more source

Decomposable Neuro Symbolic Regression

Symbolic regression (SR) models complex systems by discovering mathematical expressions that capture underlying relationships in observed data. However, most SR methods prioritize minimizing prediction error over identifying the governing equations, often producing overly complex or inaccurate expressions.
Morales, Giorgio, Sheppard, John W.
openaire   +2 more sources

Mapping Genetic Regulation of Transcription to Identify Functional Variants and Genes Associated with Pancreatic Cancer Risk

Advanced Science, EarlyView.
Integration of a pancreatic eQTL map with a GWAS meta‐analysis identifies 82 putative functional variants and 15 genes. The association between rs11102484 and pancreatic cancer risk is observed in a total of 5699 cases and 8467 controls. The G allele of rs11102484 weakens ZNF263 binding and the silencer‐promoter interaction, thereby increasing ST7L ...
Xiaoyang Wang, Hui Geng, Zhengyan Yao, Yuan Jiang, Can Chen, Zequn Lu, Shuangshuang Tian, Ming Zhang, Ruiyan Liu, Chenxi Feng, Bin Li, Xiaoping Miao, Jianbo Tian, Shaokai Zhang, Ying Zhu   +14 more
wiley   +1 more source

A Data-driven Approach for Star Formation Parameterization Using Symbolic Regression

The Astrophysical Journal
Star formation (SF) in the interstellar medium (ISM) is fundamental to understanding galaxy evolution and planet formation. However, efforts to develop closed-form analytic expressions that link SF with key influencing physical variables, such as gas ...
Diane M. Salim, Matthew E. Orr, Blakesley Burkhart, Rachel S. Somerville, Miles Cramner   +4 more
doaj   +1 more source

Dynamic Grammar Pruning for Program Size Reduction in Symbolic Regression. [PDF]

SN Comput Sci, 2023
Ali MS, Kshirsagar M, Naredo E, Ryan C.
europepmc   +1 more source

Fast Symbolic Regression Benchmarking

Symbolic regression (SR) uncovers mathematical models from data. Several benchmarks have been proposed to compare the performance of SR algorithms. However, existing ground-truth rediscovery benchmarks overemphasize the recovery of "the one" expression form or rely solely on computer algebra systems (such as SymPy) to assess success.
openaire   +2 more sources

Non‐Targeting shRNA‐Encoded Plasmid DNA Enhances Protective Immunity Through RIDD‐RIG‐I Signaling Pathway in the Zika Virus Animal Model

Advanced Science, EarlyView.
We present a novel DNA vaccine platform featuring intrinsic, non‐targeting dsRNA that significantly enhances immune responses by activating the regulated IRE1‐dependent decay‐RIG‐I signaling pathway. This research elucidates a previously uncharacterized mechanism for dsRNA‐mediated innate immune activation.
Min‐Syuan Huang, Hung‐Chun Liao, Po Peng, Wan‐Ling Wu, Kit Man Chai, Mei‐Yu Chen, Guann‐Yi Yu, Tsung‐Hsien Chuang, Hsin‐Wei Chen, Chuang‐Rung Chang, Shih‐Jen Liu   +10 more
wiley   +1 more source

Artificial Intelligence in Physical Sciences: Symbolic Regression Trends and Perspectives. [PDF]

Arch Comput Methods Eng, 2023
Angelis D, Sofos F, Karakasidis TE.
europepmc   +1 more source