Results 121 to 130 of about 1,244,223 (283)

Phenotypic and genotypic characterization of single circulating tumor cells in the follow‐up of high‐grade serous ovarian cancer

Molecular Oncology, EarlyView.
Single circulating tumor cells (sCTCs) from high‐grade serous ovarian cancer patients were enriched, imaged, and genomically profiled using WGA and NGS at different time points during treatment. sCTCs revealed enrichment of alterations in Chromosomes 2, 7, and 12 as well as persistent or emerging oncogenic CNAs, supporting sCTC identity.
Carolin Salmon, Rui P. L. Neves, Nikolas H. Stoecklein, Sven‐Thorsten Liffers, Jens Siveke, Jan D. Kuhlmann, Pauline Wimberger, Paul Buderath, Rainer Kimmig, Sabine Kasimir‐Bauer   +9 more
wiley   +1 more source

Combining antibody conjugates with cytotoxic and immune‐stimulating payloads maximizes anti‐cancer activity

Molecular Oncology, EarlyView.
Methods to improve antibody–drug conjugate (ADC) treatment durability in cancer therapy are needed. We utilized ADCs and immune‐stimulating antibody conjugates (ISACs), which are made from two non‐competitive antibodies, to enhance the entry of toxic payloads into cancer cells and deliver immunostimulatory agents into immune cells.
Tiexin Wang, Dong Jun Koo, Peter M. Tessier, Greg M. Thurber   +3 more
wiley   +1 more source

Feature-Based Dataset Fingerprinting for Clustered Federated Learning on Medical Image Data

Applied Artificial Intelligence
Federated Learning (FL) allows multiple clients to train a common model without sharing their private training data. In practice, federated optimization struggles with sub-optimal model utility because data is not independent and identically distributed (
Daniel Scheliga, Patrick Mäder, Marco Seeland   +2 more
doaj   +1 more source

Tumor mutational burden as a determinant of metastatic dissemination patterns

Molecular 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, Andrea Moreno‐Manuel, Miguel Salvadó‐Pertierra, Cristina Santos‐Vivas, Rebeca Sanz‐Pamplona   +4 more
wiley   +1 more source

Clustered Comparative Analysis of Security Sensor Discrimination Data [PDF]

Annals of computer science and information systems, 2017
Neeraj Bhargava, Aakanksha Jain, Abhishek Kumar, Pramod Singh Rathore, Anuja Bansal   +4 more
doaj   +1 more source

Rank correlation inferences for clustered data with small sample size. [PDF]

Stat Neerl, 2022
Hunsberger S, Long L, Reese SE, Hong GH, Myles IA, Zerbe CS, Chetchotisakd P, Shih JH.   +7 more
europepmc   +1 more source

Circular RNA expression landscapes in myelodysplastic neoplasms: Associations with mutational signatures and disease progression

Molecular Oncology, EarlyView.
In this explorative study, the abundance of circular RNA molecules in bone marrow stem cells was found to be elevated in patients with high‐risk myelodysplastic neoplasms, and to be associated with an increased risk of progression to acute myeloid leukemia.
Eileen Wedge, Morten Tulstrup, Gabriele Todisco, Pedro Moura, Christophe Côme, Jakob Werner Hansen, Jakob Schmidt Jespersen, Balthasar Schlotmann, Maria Creignou, Mette Dahl, Claudia Schöllkopf, Klas Raaschou‐Jensen, Krister Wennerberg, Bo Porse, Joachim Weischenfeldt, Eva Hellström‐Lindberg, Lasse Sommer Kristensen, Kirsten Grønbæk   +17 more
wiley   +1 more source

The efficient design of Nested Group Testing algorithms for disease identification in clustered data. [PDF]

J Appl Stat, 2023
Best AF, Malinovsky Y, Albert PS.
europepmc   +1 more source

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

Molecular 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

Dynamic Optimistic Ensemble Clustered Feature Selection Techniques for Big Data Analysis

Journal of Electrical and Computer Engineering
Feature selection and clustering are essential for managing high-dimensional datasets efficiently. The machine learning model performance can be improved by utilizing only the most relevant features and minimizing computational needs through feature ...
Ikram Uddin, Sandhya Avasthi, Suman Lata Tripathi, Inung Wijayanto   +3 more
doaj   +1 more source