Results 81 to 90 of about 866,547 (282)

ATF4‐mediated stress response as a therapeutic vulnerability in chordoma

open access: yesMolecular Oncology, EarlyView.
We screened 5 chordoma cell lines against 100+ inhibitors of epigenetic and metabolic pathways and kinases and identified halofuginone, a tRNA synthetase inhibitor. Mechanistically halofuginone induces an integrated stress response, with eIF2alpha phosphorylation, activation of ATF4 and its target genes CHOP, ASNS, INHBE leading to cell death ...
Lucia Cottone   +11 more
wiley   +1 more source

Laplacian Centrality Peaks Clustering Based on Potential Entropy

open access: yesIEEE Access, 2018
The clustering analysis is an important unsupervised learning algorithm in data mining, which has a wide range of applications in the field of pattern recognition, image processing, and so on. The existing clustering algorithms generally need one or more
Xu-Hua Yang   +5 more
doaj   +1 more source

Unsupervised K-Means Clustering Algorithm

open access: yesIEEE Access, 2020
The k-means algorithm is generally the most known and used clustering method. There are various extensions of k-means to be proposed in the literature. Although it is an unsupervised learning to clustering in pattern recognition and machine learning, the
Kristina P. Sinaga, Miin-Shen Yang
doaj   +1 more source

LDAcoop: Integrating non‐linear population dynamics into the analysis of clonogenic growth in vitro

open access: yesMolecular Oncology, EarlyView.
Limiting dilution assays (LDAs) quantify clonogenic growth by seeding serial dilutions of cells and scoring wells for colony formation. The fraction of negative wells is plotted against cells seeded and analyzed using the non‐linear modeling of LDAcoop.
Nikko Brix   +13 more
wiley   +1 more source

Large Data Oriented to Image Information Fusion Spark and Improved Fruit Fly Optimization Based on the Density Clustering Algorithm

open access: yesAdvances in Multimedia, 2023
The density-based applied spatial clustering algorithm is an algorithm based on high-density interconnected regions, which discovers class clusters of arbitrary shapes in noisy data sets and is widely used. However, it suffers from slow computation speed
Yanfang Zhang
doaj   +1 more source

Infrared laser sampling of low volumes combined with shotgun lipidomics reveals lipid markers in palatine tonsil carcinoma

open access: yesMolecular Oncology, EarlyView.
Nanosecond infrared laser (NIRL) low‐volume sampling combined with shotgun lipidomics uncovers distinct lipidome alterations in oropharyngeal squamous cell carcinoma (OPSCC) of the palatine tonsil. Several lipid species consistently differentiate tumor from healthy tissue, highlighting their potential as diagnostic markers.
Leonard Kerkhoff   +11 more
wiley   +1 more source

Crucial parameters for precise copy number variation detection in formalin‐fixed paraffin‐embedded solid cancer samples

open access: yesMolecular Oncology, EarlyView.
This study shows that copy number variations (CNVs) can be reliably detected in formalin‐fixed paraffin‐embedded (FFPE) solid cancer samples using ultra‐low‐pass whole‐genome sequencing, provided that key (pre)‐analytical parameters are optimized.
Hanne Goris   +10 more
wiley   +1 more source

Tumor mutational burden as a determinant of metastatic dissemination patterns

open access: yesMolecular Oncology, EarlyView.
This study performed a comprehensive analysis of genomic data to elucidate whether metastasis in certain organs share genetic characteristics regardless of cancer type. No robust mutational patterns were identified across different metastatic locations and cancer types.
Eduardo Candeal   +4 more
wiley   +1 more source

An Adaptive Ellipse Distance Density Peak Fuzzy Clustering Algorithm Based on the Multi-target Traffic Radar

open access: yesSensors, 2020
In the multi-target traffic radar scene, the clustering accuracy between vehicles with close driving distance is relatively low. In response to this problem, this paper proposes a new clustering algorithm, namely an adaptive ellipse distance density peak
Lin Cao   +4 more
doaj   +1 more source

RaMBat: Accurate identification of medulloblastoma subtypes from diverse data sources with severe batch effects

open access: yesMolecular Oncology, EarlyView.
To integrate multiple transcriptomics data with severe batch effects for identifying MB subtypes, we developed a novel and accurate computational method named RaMBat, which leveraged subtype‐specific gene expression ranking information instead of absolute gene expression levels to address batch effects of diverse data sources.
Mengtao Sun, Jieqiong Wang, Shibiao Wan
wiley   +1 more source

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