Results 121 to 130 of about 110,857 (196)

Cis‐ and Trans‐Regulatory Factors Independently Shape Phenotypic Heterogeneity of Retinitis Pigmentosa

Advanced Science, EarlyView.
A zebrafish model carrying an identical human RHO S334X allele reveals two independent genetic layers shaping retinitis pigmentosa (RP) severity: a protective 3‐bp cis‐regulatory insertion that attenuates transgene expression, and a dominant trans‐acting modifier that restores a severe phenotype.
Cong Cui, Kotone Nakagawa, Takumi Tateno, Ayaka Dan, Dexin Meng, Yoshihiro Omori, Soma Tomihara, Suzuri Okamoto, Shigeru Sato, Motokazu Tsujikawa   +9 more
wiley   +1 more source

Construction of complex and diverse DNA sequences using DNA three-way junctions. [PDF]

Nature
Robinson NE, Zhang W, Ghosh R, Gerber B, Zhang H, Sanfiorenzo C, Wang S, Di Carlo D, Wang K.   +8 more
europepmc   +1 more source

The ITGB2‐COPS3‐SOX2 Axis and SOX2 Liquid‐Liquid Phase Separation: Dual Mechanisms Governing Osteosarcoma Stemness

Advanced Science, EarlyView.
Osteosarcoma stemness is driven by the ITGB2‐COPS3‐SOX2 signaling axis. This study reveals that nuclear COPS3 stabilizes SOX2, which in turn undergoes liquid‐liquid phase separation to promote stemness. Based on this mechanism, a novel COPS3 inhibitor, Z‐5891, was developed, effectively suppressing tumor growth and stemness in vivo, offering a ...
Lei Guo, Zhiqing Zhao, Wei Wang, Jianfang Niu, Bing Wang, Yunfei Lin, Wei Guo, Taiqiang Yan   +7 more
wiley   +1 more source

Machine‐Learning Microfluidic Minute‐Scale Microorganism Metrics Monitoring(M6)

Advanced Science, EarlyView.
ABSTRACT On‐site monitoring of microorganisms remains challenging because of low concentrations, strong background interference, and dynamic aerosol diffusion, particularly for aerosol‐transmitted pathogens. Here, we report a rapid detection platform that integrates a Puri‐focusing microfluidic chip, electrochemical impedance spectroscopy (EIS), and ...
Ning Yang, Jiahao Ding, Si Chen, Lijie Yan, Shichao Ding, Lavonda Li, Junyi Sun, Haodong Liu, Tongge Li, Ning Liu, Mingji Wei, Xiaoyong Zhu, Xiaobo Zou, Shouqi Yuan, Xingcai Zhang   +14 more
wiley   +1 more source

Multimodal bioinformatic analyses of genome-scale expression beyond gene-centric differential expression. [PDF]

Brief Bioinform
Nuanpirom J, Charoensawan V.
europepmc   +1 more source

Persistently Increased Expression of PKMzeta and Unbiased Gene Expression Profiles Identify Hippocampal Molecular Traces of a Long‐Term Active Place Avoidance Memory and “Shadow” Proteins

Advanced Science, EarlyView.
Protein complexes like KIBRA‐PKMζ are crucial for maintaining memories, forming month‐long protein traces in memory‐tagged neurons, but conventional RNA‐seq analysis fails to detect their transcript changes, leaving memory molecules undetected in the shadows of abundantly‐expressed genes.
Jiyeon Han, Alejandro Grau‐Perales, Rayna M. Harris, Edith Lesburguères, Hsin‐Yi Kao, Asit Pal, Juan Marcos Alarcon, Todd C. Sacktor, Stefano Martiniani, Hans A. Hofmann, André A. Fenton   +10 more
wiley   +1 more source

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

PyOrthoANI, PyFastANI, and Pyskani: a suite of Python libraries for computation of average nucleotide identity. [PDF]

NAR Genom Bioinform
Larralde M, Zeller G, Carroll LM.
europepmc   +1 more source

An Integrated NLP‐ML Framework for Property Prediction and Design of Steels

Advanced Science, EarlyView.
This study presents a data‐driven framework that uses language‐processing techniques to interpret steel processing descriptions and machine‐learning models to predict mechanical properties. By organising complex process histories into meaningful groups and enabling rapid property forecasts, the work supports faster, more informed steel design through ...
Kiran Devraju, Adithya Umanath Rai, Jose Thomson, Marzie Ghorbani, Shujing Zhao, Nick Birbilis   +5 more
wiley   +1 more source

MXtalTools: A Toolkit for Machine Learning on Molecular Crystals. [PDF]

J Chem Inf Model
Kilgour M, Tuckerman ME, Rogal J.
europepmc   +1 more source