Results 111 to 120 of about 8,013,557 (321)

Overview of molecular signatures of senescence and associated resources: pros and cons

open access: yesFEBS Open Bio, EarlyView.
Cells can enter a stress response state termed cellular senescence that is involved in various diseases and aging. Detecting these cells is challenging due to the lack of universal biomarkers. This review presents the current state of senescence identification, from biomarkers to molecular signatures, compares tools and approaches, and highlights ...
Orestis A. Ntintas   +6 more
wiley   +1 more source

EncoderMap: Dimensionality Reduction and Generation of Molecule Conformations.

open access: yesJournal of Chemical Theory and Computation, 2019
Molecular simulation is one example where large amounts of high-dimensional (high-d) data are generated. To extract useful information, e.g., about relevant states and important conformational transitions, a form of dimensionality reduction is required ...
Tobias Lemke, C. Peter
semanticscholar   +1 more source

Impact of a senior research thesis on students' perceptions of scientific inquiry in distinct student populations

open access: yesFEBS Open Bio, EarlyView.
This study addressed how a senior research thesis is perceived by undergraduate students. It assessed students' perception of research skills, epistemological beliefs, and career goals in Biochemistry (science) and BDC (science‐business) students. Completing a thesis improved confidence in research skills, resilience, scientific identity, closed gender‐
Celeste Suart   +4 more
wiley   +1 more source

DDX3X induces mesenchymal transition of endothelial cells by disrupting BMPR2 signaling

open access: yesFEBS Open Bio, EarlyView.
Elevated DDX3X expression led to downregulation of BMPR2, a key regulator of endothelial homeostasis and function. Our co‐immunoprecipitation assays further demonstrated a molecular interaction between DDX3X and BMPR2. Notably, DDX3X promoted lysosomal degradation of BMPR2, thereby impairing its downstream signaling and facilitating endothelial‐to ...
Yu Zhang   +7 more
wiley   +1 more source

Exploring the Influence of Dimensionality Reduction on Anomaly Detection Performance in Multivariate Time Series

open access: yesIEEE Access
This paper presents an extensive empirical study on the integration of dimensionality reduction techniques with advanced unsupervised time series anomaly detection models, focusing on the MUTANT and Anomaly-Transformer models.
Mahsun Altin, Altan Cakir
doaj   +1 more source

Antibiofilm activity of a chionodracine‐derived peptide by NMR‐based metabolomics of cell‐free supernatant of Acinetobacter baumannii clinical strains

open access: yesFEBS Open Bio, EarlyView.
KHS‐Cnd peptide is able to impair biofilm formation and disaggregate mature biofilms in Acinetobacter baumannii clinical isolates. Differences in extracellular metabolites reflect changes in biofilm metabolism due to KHS‐Cnd treatment. Among the differentially represented extracellular metabolites upon KHS‐Cnd treatment, the significantly altered ...
Fernando Porcelli   +9 more
wiley   +1 more source

Dimensionality Reduction via Multiple Locality-Constrained Graph Optimization

open access: yesIEEE Access, 2018
In recent years, graph-based dimensionality reduction methods became increasingly more significant since they have been successfully applied in various computer vision and machine learning problems.
Caixia Zheng   +6 more
doaj   +1 more source

Automated FRAP microscopy for high‐throughput analysis of protein dynamics in chromatin organization and transcription

open access: yesFEBS Open Bio, EarlyView.
RoboMic is an automated confocal microscopy pipeline for high‐throughput functional imaging in living cells. Demonstrated with fluorescence recovery after photobleaching (FRAP), it integrates AI‐driven nuclear segmentation, ROI selection, bleaching, and analysis.
Selçuk Yavuz   +6 more
wiley   +1 more source

Cascade Support Vector Machines with Dimensionality Reduction

open access: yesApplied Computational Intelligence and Soft Computing, 2015
Cascade support vector machines have been introduced as extension of classic support vector machines that allow a fast training on large data sets. In this work, we combine cascade support vector machines with dimensionality reduction based preprocessing.
Oliver Kramer
doaj   +1 more source

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