Results 51 to 60 of about 11,210,090 (249)

Prospecting the protein design landscape

FEBS Letters, EarlyView.
This review outlines the current state of various protein design approaches. We discuss the current possibilities enabled by recently released tools, highlight future avenues to pursue in protein design, and underscore the crucial role of key databases and resources for successful protein design workflows.
Jakob R. Riccabona, Katharina T. Stonig, Jens Meiler, Clara T. Schoeder, Monica L. Fernández‐Quintero   +4 more
wiley   +1 more source

MSF-LCC: multi-scale spatial-frequency feature learning framework for land cover classification from cross-domain datasets

Geo-spatial Information Science
Land cover classification is essential for sustainable development but remains challenging due to the complexity of high-resolution remote sensing imagery, including spectral similarity between objects, variability within objects, and uneven spatial ...
Bo Yu, Zhihui Ou, Fang Chen, Lei Wang, Ning Wang   +4 more
doaj   +1 more source

Soft motions encoded by the fold and mediated by conserved hinge sites drive V‐ATPase allosteric machinery and autoinhibition

FEBS Letters, EarlyView.
Vacuolar H+‐ATPase (V‐ATPase) is a multisubunit rotary proton pump that acidifies intracellular compartments. Using elastic network models, we identified conserved hinge residues that govern its large‐scale functional motions. We show that intrinsically encoded ‘soft modes’ drive critical functional transitions, including rotary catalysis and ...
Diksha Parwana, Xiaowei Bogetti, Stuti Sharma, Ivet Bahar   +3 more
wiley   +1 more source

Time-series representation learning via Time-Frequency Fusion Contrasting

Frontiers in Artificial Intelligence
Time series is a typical data type in numerous domains; however, labeling large amounts of time series data can be costly and time-consuming. Learning effective representation from unlabeled time series data is a challenging task.
Wenbo Zhao, Ling Fan
doaj   +1 more source

Robust PD-Type Iterative Learning Control of Discrete Linear Repetitive Processes in the Finite Frequency Domain

Mathematics, 2020
This paper studies a robust iterative learning control design for discrete linear repetitive processes in the finite frequency domain. Firstly, the state-space model of the iterative learning process is deduced.
Lei Wang, Mu Li, Huizhong Yang
doaj   +1 more source

Side-channel analysis in frequency domain with clustering

Dianzi Jishu Yingyong, 2021
The alignment of power traces is one of the key factors affecting the success of side-channel analysis. Frequency-domain side-channel analysis can effectively solve the alignment of power traces in the time domain.
Cai Juesong, Yan Yingjian, Zhu Chunsheng, Guo Pengfei   +3 more
doaj   +1 more source

CEACAM1 participation in breast cancer progression

Molecular Oncology, EarlyView.
In invasive breast cancer (BC), CEACAM1 shifts from an apical to a uniform membranous/cytoplasmic pattern, or is lost, as tumors dedifferentiate, inversely tracking the Ki‐67 proliferative index. In MCF‐7 cells, only CEACAM1‐4L suppresses proliferation, repressing cell cycle and growth factor genes.
Mykola Lyndin, Irina Kube‐Golovin, Anatolii Romaniuk, Gunther Wennemuth   +3 more
wiley   +1 more source

Frequency-domain pairs of BRIC and G7 equities.

, 2022
Frequency-domain pairs of BRIC and G7 equities.
Anokye Mohammed Adam (13162733), Emmanuel Asafo-Adjei (223154), Peterson Owusu Junior (13019411), Ahmed Bossman (13162727), Samuel Kwaku Agyei (13162724), Oliver Asiamah (13162730)   +5 more
core   +1 more source

Partial FAK suppression promotes tumor growth, an effect reversed by macrophage p110δ PI3K inactivation

Molecular Oncology, EarlyView.
Partial inhibition of focal adhesion kinase (FAK) can paradoxically promote tumor growth, rather than simply producing a weaker antitumor effect than that observed with strong FAK suppression. In breast cancer and melanoma models, targeting p110δ PI3K, particularly in macrophages, counteracted these tumor‐promoting effects, highlighting the importance ...
Lydia Xenou, Niki Tzenaki, Anna Tsapara, Maria Tzardi, Evangelia A. Papakonstanti   +4 more
wiley   +1 more source

Frequency-domain Learning for Volumetric-based 3D Data Perception

, 2023
Frequency-domain learning draws attention due to its superior tradeoff between inference accuracy and input data size. Frequency-domain learning in 2D computer vision tasks has shown that 2D convolutional neural networks (CNN) have a stationary spectral ...
Yu, Zifan, Ren, Fengbo, You, Suya
core