Results 51 to 60 of about 112,189 (262)

Efficient State Estimation Through Rapid Topological Analysis Based on Spatiotemporal Graph Methodology

IEEE Open Access Journal of Power and Energy
The seamless integration of swift and precise topological analysis with state estimation is crucial for ensuring the dependability, stability, and efficiency of the power system.
Zhen Dai, Shouyu Liang, Yachen Tang, Jun Tan, Guangyi Liu, Qinyu Feng, Xuanang Li   +6 more
doaj   +1 more source

Applications of Parameterized st-Orientations

Journal of Graph Algorithms and Applications, 2010
An st-orientation of a biconnected undirected graph defines a directed graph with no cycles, a single source s and a single sink t. Given an undirected graph G as input, linear-time algorithms have been proposed for computing an st-orientation of G. Such
Charalampos Papamanthou, Ioannis Tollis
doaj   +1 more source

Functional comparison of EncB and EncC cargo proteins in iron storage within the Myxococcus xanthus encapsulin

FEBS Letters, EarlyView.
Encapsulins are protein nanocompartments that play an important role in iron storage. In the Myxococcus xanthus encapsulin system, two cargo proteins called EncB and EncC contribute to iron mineralization. Here, we show that EncB and EncC generate iron‐containing minerals with distinct chemical compositions, suggesting that the composition of stored ...
Harry B. McDowell, Thomas Walther, Egbert Hoiczyk   +2 more
wiley   +1 more source

Logspace computations in graph products [PDF]

Journal of Symbolic Computation, 2014
We consider three important and well-studied algorithmic problems in group theory: the word, geodesic, and conjugacy problem. We show transfer results from individual groups to graph products. We concentrate on logspace complexity because the challenge is actually in small complexity classes, only.
Volker Diekert, Jonathan Kausch
openaire   +5 more sources

Graph Computing Based Knowledge Reasoning in Electric Power System Considering Knowledge Graph Sparsity

CSEE Journal of Power and Energy Systems
Knowledge graph, which is a rapidly developing technology, provides strong support in business and engineering. Knowledge graph plays an important role in recommendations and decision-making, while in the electric power industry, there would be more ...
Tianjiao Pu, Yuanpeng Tan, Zhenyuan Ma, Jiannan Xu   +3 more
doaj   +1 more source

Using Multidimensional Matrices to Determine Graph Properties

Современные информационные технологии и IT-образование, 2022
The need to determine the most appropriate data model increases, as the complexity of the designed computing systems and computer networks increases. The graph model is one of the main models for this kind of tasks.
Aleksandr Makarov, Victor Munerman
doaj   +1 more source

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

A context‐dependent modulatory role for eIF6 in acquired resistance to vemurafenib in melanoma

FEBS Letters, EarlyView.
Acquired resistance to vemurafenib upregulates the translation factor eIF6 in melanoma cells. Silencing eIF6 in resistant cells reduces proliferation and partially restores drug sensitivity, whereas its overexpression increases sensitivity across melanoma lines regardless of BRAF status, via modulation of mTOR, S6K, and MAPK signaling.
George Kyriakopoulos, Antonia Petropoulou, Alexandra Anastogianni, Angelina Bania, Vassilis Stamatakis, Argyris Alexiou, Chi‐Ping Day, Glenn Merlino, Katerina Grafanaki, Constantinos Stathopoulos   +9 more
wiley   +1 more source

Parallelizing Sequential Graph Computations [PDF]

ACM Transactions on Database Systems, 2018
This article presents GRAPE, a parallel <underline>GRAP</underline>h <underline>E</underline>ngine for graph computations. GRAPE differs from prior systems in its ability to parallelize existing sequential graph algorithms as a whole, without the need for recasting the entire algorithm into a new model.
Wenfei Fan, Wenyuan Yu, Jingbo Xu 0001, Jingren Zhou 0001, Xiaojian Luo, Qiang Yin 0002, Ping Lu 0005, Yang Cao 0012, Ruiqi Xu 0002   +8 more
openaire   +2 more sources

Scalable training of graph convolutional neural networks for fast and accurate predictions of HOMO-LUMO gap in molecules

Journal of Cheminformatics, 2022
Graph Convolutional Neural Network (GCNN) is a popular class of deep learning (DL) models in material science to predict material properties from the graph representation of molecular structures.
Jong Youl Choi, Pei Zhang, Kshitij Mehta, Andrew Blanchard, Massimiliano Lupo Pasini   +4 more
doaj   +1 more source