Results 111 to 120 of about 178,314 (358)

Coping With New Challengens for Density-Based Clustering [PDF]

, 2004
Knowledge Discovery in Databases (KDD) is the non-trivial process of identifying valid, novel, potentially useful, and ultimately understandable patterns in data.
Kröger, Peer
core  

A light‐triggered Time‐Resolved X‐ray Solution Scattering (TR‐XSS) workflow with application to protein conformational dynamics

FEBS Open Bio, EarlyView.
Time‐resolved X‐ray solution scattering captures how proteins change shape in real time under near‐native conditions. This article presents a practical workflow for light‐triggered TR‐XSS experiments, from data collection to structural refinement. Using a calcium‐transporting membrane protein as an example, the approach can be broadly applied to study ...
Fatemeh Sabzian‐Molaei, Fredrik Orädd, Konstantinos Magkakis, Magnus Andersson   +3 more
wiley   +1 more source

Capped $l_1$ -Norm Sparse Representation Method for Graph Clustering

IEEE Access, 2019
As one of the most popular clustering techniques, graph clustering has attracted many researchers in the field of machine learning and data mining. Generally speaking, graph clustering partitions the data points into different categories according to ...
Mulin Chen, Qi Wang, Shangdong Chen, Xuelong Li   +3 more
doaj   +1 more source

Spectral Clustering by Subspace Randomization and Graph Fusion for High-Dimensional Data [PDF]

, 2020
Xiaosha Cai, Dong Huang, Chang‐Dong Wang, Chee-Keong Kwoh   +3 more
openalex   +1 more source

Single‐molecule DNA flow‐stretch assays for high‐throughput DNA–protein interaction studies

FEBS Open Bio, EarlyView.
We describe an optimised single‐molecule DNA flow‐stretch assay that visualises DNA–protein interactions in real time. Linear DNA fragments are tethered to a surface and stretched by buffer flow for fluorescence imaging. Using λ and φX174 DNA, this protocol enhances reproducibility and accessibility, providing a versatile approach for studying diverse ...
Ayush Kumar Ganguli, Mohammad Nour Alsamsam, Ugnė Bagdonaitė, Van Truc Vu, Chun‐Jen Huang, Polina Kuzhir, Mindaugas Zaremba, Aurimas Kopūstas, Marijonas Tutkus   +8 more
wiley   +1 more source

Deep Graph Clustering with Triple Fusion Mechanism for Community Detection

Deep graph clustering is a highly significant tool for community detection, enabling the identification of strongly connected groups of nodes within a graph. This technology is crucial in various fields such as education and E-learning.
Shi, Kaize, Zhang, Peng, Zhang, P, Peng, Xueping, Liu, Jinyan, Lei, Zhongxiang, Niu, Zhendong, Shi, K, Ma, Yuanchi, He, H, Liu, J, Ma, Y, Lei, Z, Niu, Z, He, Hui, Peng, X   +15 more
core   +1 more source

Comparison and Benchmark of Graph Clustering Algorithms [PDF]

, 2020
Lizhen Shi, Bo Chen
openalex   +1 more source

Analysing the significance of small conformational changes and low occupancy states in serial crystallographic data

FEBS Open Bio, EarlyView.
This protocol paper outlines methods to establish the success of a time‐resolved serial crystallographic experiment, by means of statistical analysis of timepoint data in reciprocal space and models in real space. We show how to amplify the signal from excited states to visualise structural changes in successful experiments.
Jake Hill, Yelyzaveta Pulnova, Elke De Zitter, Helen M. Ginn, Briony A. Yorke   +4 more
wiley   +1 more source

Graph Clustering Using Distance-k Cliques

, 1999
Identifying the natural clusters of nodes in a graph and treating them as supernodes or metanodes for a higher level graph (or an abstract graph) is a technique used for the reduction of visual complexity of graphs with a large number of nodes.
Brandenburg, Franz J., Jubin Edachery, Franz J. Brandenburg, Edachery, Jubin, Sen, Arunabha, Arunabha Sen   +5 more
core   +1 more source

MiR‐513a promotes human erythroid differentiation by modulating c‐Jun

FEBS Open Bio, EarlyView.
During early human erythropoiesis, miR‐513a promoted erythroid differentiation in primary human CD34+ hematopoietic stem‐progenitor cells and human TF‐1 erythroleukemic cells by indirectly decreasing c‐Jun and phospho‐c‐Jun expression, which are associated with increased GATA1 expression.
MinJung Kim, Brittany Taylor, Shannon Bolten, Christian L. Eberly, Mahliya Abdurahman, T. Michael Creed, Acong Yang, Taylor L. Hatchet, Tristan Dyson, Shuo Gu, Curt I. Civin, Tami J. Kingsbury   +11 more
wiley   +1 more source