Results 41 to 50 of about 1,803,229 (305)

Advancing Federated Learning with Granular Computing

Fuzzy Information and Engineering, 2023
Over the recent years, we have been witnessing spectacular achievements of Artificial Intelligence (AI) and Machine Learning (ML), in particular. We have seen highly visible accomplishments encountered in natural language processing and computer vision ...
Witold Pedrycz
doaj   +1 more source

Ligand‐dependent transcriptional heterogeneity in cell cycle gene expression delays G1/S entry

FEBS Letters, EarlyView.
EGF and HRG induce distinct G1/S progression programs in ErbB2‐amplified BT474 breast cancer cells. Despite activating the potent ErbB2–ErbB3 heterodimer, HRG does not accelerate cell‐cycle entry. Instead, EGF promotes earlier restriction‐point passage via ERK–FOS signaling, whereas HRG activates the AKT–MYC axis, driving transcriptional heterogeneity ...
Ririn Rahmala Febri, Ayaka Nagasato‐Ichikawa, Keita Iida, Shuhei Kimura, Akira Imamoto, Mariko Okada   +5 more
wiley   +1 more source

Granular computing on basic digraphs

Applicable Analysis and Discrete Mathematics, 2022
In the present paper we investigate (p, q)-directed complete bipartite graphs ?K p,q, n-directed paths ?Pn and n-directed cycles ?C n from the perspective of Granular Computing. For each model, we establish the general form of all possible indiscernibility relations, analyze the classical rough approximation functions of rough set theory and provide a ...
Chiaselotti G., Gentile T., Infusino F.
openaire   +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

Wind Power Prediction Based on a Hybrid Granular Chaotic Time Series Model

Frontiers in Energy Research, 2022
For realizing high-accuracy short-term wind power prediction, a hybrid model considering physical features of data is proposed in this paper, with consideration of chaotic analysis and granular computing.
Yanyang Wang, Wei Xiong, Shiping E., Qingguo Liu, Nan Yang, Ping Fu, Kang Gong, Yu Huang   +7 more
doaj   +1 more source

Spatial and single‐nuclei transcriptomics reveals idiosyncratic and generic patterns in papillary and anaplastic thyroid cancers

Molecular Oncology, EarlyView.
Matched spatial transcriptomics and single‐nuclei RNA‐seq were generated for anaplastic and BRAFV600E papillary thyroid cancers revealing generic and tumor‐specific states occurring in cancer cells and in the tumor microenvironment. In this context, cancer dedifferentiation mirrored organoid maturation through ordered thyroid marker gain/loss ...
Adrien Tourneur, Joel Rodrigues Vitória, Manuel Saiselet, Ligia Craciun, Denis Larsimont, Anne Lefort, Frédérick Libert, Carine Maenhaut, Sabine Costagliola, Maxime Tarabichi, Mirian Romitti, Vincent Detours   +11 more
wiley   +1 more source

Quantitative analysis for image segmentation by granular computing clustering from the view of set

Journal of Algorithms & Computational Technology, 2019
As partition method of set, granular computing clustering is applied to image segmentation evaluated by global consistency error, variation of Information, and Rand index from the view of set.
Hongbing Liu, Xiaoyu Diao, Huaping Guo
doaj   +1 more source

Information structures in an incomplete information system: A granular computing viewpoint

International Journal of Computational Intelligence Systems, 2018
Granular computing is a essential mathematical tool in artificial intelligence. An incomplete information system is an important model and its basic structures are information structures.
Guangji Yu
doaj   +1 more source

In vitro and in silico modelling of ROS1‐positive non‐small cell lung cancer reveals fusion‐dependent tyrosine kinase inhibitor responses

Molecular Oncology, EarlyView.
Drug resistance limits treatment success in a subset of lung cancers driven by ROS1 gene alterations. Using patient‐derived cells and computer simulations, we studied three key mutations and how they affect five targeted drugs. The mutations reduced drug effectiveness in different ways by altering protein structure and behavior.
Farhan Ul Haq, Marc Terrones, Felicia Rodrigues Fortes, Anne Schepers, Alessia Denis, Christophe Deben, Ken Op de Beeck, Guy Van Camp, Geert Vandeweyer   +8 more
wiley   +1 more source

A Granular Computing-Based Deep Neural Network Approach for Automatic Evaluation of Writing Quality

IEEE Access, 2023
As a subjective behaviour relying on expert experience, automatic evaluation of writing quality always remains a technical issue. It requires both effective semantic understanding and structure analysis towards writing contents.
Majun Ge
doaj   +1 more source