Results 161 to 170 of about 940,524 (345)

Research on Automatic Alignment for Corn Harvesting Based on Euclidean Clustering and K-Means Clustering

open access: yesAgriculture
Aiming to meet the growing need for automated harvesting, an automatic alignment method based on Euclidean clustering and K-means clustering is proposed to address issues of driver fatigue and inaccurate driving in manually operated corn harvesters ...
Bin Zhang   +9 more
doaj   +1 more source

Interpreting the effects of DNA polymerase variants at the structural level

open access: yesMolecular Oncology, EarlyView.
Using MAVISp and molecular dynamics simulations, we analyzed over 60 000 missense variants in POLE and POLD1 from ClinVar, COSMIC, cBioPortal, and saturation mutagenesis. Identified mechanistic indicators, including stability, binding, and long‐range, enable structural interpretation, providing ACMG‐like evidence for possible reclassification of VUS ...
Matteo Arnaudi   +7 more
wiley   +1 more source

A cross dataset meta-model for hepatitis C detection using multi-dimensional pre-clustering

open access: yesScientific Reports
Hepatitis C is a liver infection triggered by the hepatitis C virus (HCV). The infection results in swelling and irritation of the liver, which is called inflammation. Prolonged untreated exposure to the virus can lead to chronic hepatitis C.
Aryan Sharma   +2 more
doaj   +1 more source

Developmental programmes drive cellular plasticity, disease progression and therapy resistance in lung adenocarcinoma

open access: yesMolecular Oncology, EarlyView.
This study shows that lung adenocarcinomas exploit developmental branching morphogenesis to acquire a therapy resistant basal‐like tumour cell state. This process was found to be regulated by combined TP53 loss‐of‐function and type‐I interferon signalling, identifying a novel axis for biomarker and therapeutic target discovery.
Kamila J Bienkowska   +13 more
wiley   +1 more source

Flow Enabled Target Capture Halbach‐based magnetic enrichment increases circulating tumor cell capture from blood in metastatic cancer patients

open access: yesMolecular Oncology, EarlyView.
Pair‐wise comparison of the CellSearch and FETCH enrichment technologies for circulating tumor cells (CTCs) from metastatic breast, prostate, and small cell lung cancer patients shows an increased capture of CTCs using FETCH enrichment. The clinical implementation of circulating tumor cells (CTCs) as a predictive tool for therapy efficacy in the ...
Michiel Stevens   +6 more
wiley   +1 more source

Bilateral K - Means algorithm for fast co-clustering

open access: yes, 2017
With the development of the information technology, the amount of data, e.g. text, image and video, has been increased rapidly. Efficiently clustering those large scale data sets is a challenge.
Han, Junwei   +4 more
core   +1 more source

A novel quinazolinone insulin receptor inhibitor and its synergy with an EGFR inhibitor in glucose‐driven glioblastoma

open access: yesMolecular Oncology, EarlyView.
The novel styrylquinazolinone‐based molecule W1B effectively suppresses glioblastoma by inhibiting IGF1R and EGFR. In high‐glucose microenvironments driving tumor resistance, W1B acts synergistically with the EGFR inhibitor dacomitinib. This combination safely blocks compensatory survival signaling in zebrafish xenograft models. Showcasing promising in
Patryk Rurka   +9 more
wiley   +1 more source

A study on learning-augmented k-means clustering

open access: yes
reservedClustering is a practical approach for extracting meaningful information from unstructured data. With the exponential growth of data, it is essential to develop efficient methods for computing clusters.
PEPAJ, MARIA TERESA
core  

An efficient k-modes algorithm for clustering categorical datasets

open access: yes, 2022
Mining clusters from data is an important endeavor in many applications. The k-means method is a popular, efficient, and distribution-free approach for clustering numerical-valued data, but does not apply for categorical-valued observations.
Maitra, Ranjan, Dorman, Karin S.
core  

Oncogenic DMTF1β promotes cancer cell motility by regulating autophagy through ULK1 stabilization

open access: yesMolecular Oncology, EarlyView.
In the current study, we demonstrate that the oncogene DMTF1β regulates ULK1 stability by reducing its proteasomal degradation in cancer cells. This stabilization enables ULK1 to induce autophagy, which in turn facilitates cancer cell migration. Consequently, reduced DMTF1β levels lead to decreased autophagy and impaired cancer cell migration.
Jun Xu   +13 more
wiley   +1 more source

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