Results 41 to 50 of about 7,778,769 (283)

Identifying gene-specific subgroups: an alternative to biclustering

BMC Bioinformatics, 2019
Background Transcriptome analysis aims at gaining insight into cellular processes through discovering gene expression patterns across various experimental conditions.
Vincent Branders, Pierre Schaus, Pierre Dupont   +2 more
doaj   +1 more source

A large‐scale retrospective study in metastatic breast cancer patients using circulating tumour DNA and machine learning to predict treatment outcome and progression‐free survival

Molecular Oncology, EarlyView.
There is an unmet need in metastatic breast cancer patients to monitor therapy response in real time. In this study, we show how a noninvasive and affordable strategy based on sequencing of plasma samples with longitudinal tracking of tumour fraction paired with a statistical model provides valuable information on treatment response in advance of the ...
Emma J. Beddowes, Mario Ortega Duran, Solon Karapanagiotis, Alistair Martin, Meiling Gao, Riccardo Masina, Ramona Woitek, James Tanner, Fleur Tippin, Justine Kane, Jonathan Lay, Anja Brouwer, Stephen‐John Sammut, Suet‐Feung Chin, Davina Gale, Dana W. Y. Tsui, Sarah‐Jane Dawson, Nitzan Rosenfeld, Maurizio Callari, Oscar M. Rueda, Carlos Caldas   +20 more
wiley   +1 more source

Data‐driven discovery of gene expression markers distinguishing pediatric acute lymphoblastic leukemia subtypes

Molecular Oncology, EarlyView.
This study investigates gene expression differences between two major pediatric acute lymphoblastic leukemia (ALL) subtypes, B‐cell precursor ALL, and T‐cell ALL, using a data‐driven approach consisting of biostatistics and machine learning methods. Following analysis of a discovery dataset, we find a set of 14 expression markers differentiating the ...
Mona Nourbakhsh, Nikola Tom, Anna Schrøder Lassen, Helene Brasch Lind Petersen, Ulrik Kristoffer Stoltze, Karin Wadt, Kjeld Schmiegelow, Matteo Tiberti, Elena Papaleo   +8 more
wiley   +1 more source

Machine learning for identifying liver and pancreas cancers through comprehensive serum glycopeptide spectra analysis: a case‐control study

Molecular Oncology, EarlyView.
This study presents a novel AI‐based diagnostic approach—comprehensive serum glycopeptide spectra analysis (CSGSA)—that integrates tumor markers and enriched glycopeptides from serum. Using a neural network model, this method accurately distinguishes liver and pancreatic cancers from healthy individuals.
Motoyuki Kohjima, Yuko Takami, Ken Kawabe, Kazuhiro Tanabe, Chihiro Hayashi, Mikio Mikami, Tetsuya Kusumoto   +6 more
wiley   +1 more source

Self-supervision advances morphological profiling by unlocking powerful image representations

Scientific Reports
Cell Painting is an image-based assay that offers valuable insights into drug mechanisms of action and off-target effects. However, traditional feature extraction tools such as CellProfiler are computationally intensive and require frequent parameter ...
Vladislav Kim, Nikolaos Adaloglou, Marc Osterland, Flavio M. Morelli, Marah Halawa, Tim König, David Gnutt, Paula A. Marin Zapata   +7 more
doaj   +1 more source

Study to Determine Levels of Cadmium in Cocoa Crops Applied to Inland Areas of Peru: “The Case of the Campo Verde-Honoria Tournavista Corridor”

Agronomy, 2020
The presence of cadmium (Cd) in cocoa crops is currently a serious problem for farmers and producers in various regions of South America. Because its exports of cocoa and derivatives to European markets are threatened by possible signs of contamination ...
Jimmy Aurelio Rosales-Huamani, Jorge Luis Breña-Ore, Svitlana Sespedes-Varkarsel, Luis Huamanchumo de la Cuba, Luis Centeno-Rojas, Alonso Otiniano-Zavala, Joseps Andrade-Choque, Santiago Valverde-Espinoza, Jose Luis Castillo-Sequera   +8 more
doaj   +1 more source

Objective criteria for explanations of machine learning models

Applied AI Letters, 2021
Objective criteria to evaluate the performance of machine learning (ML) model explanations are a critical ingredient in bringing greater rigor to the field of explainable artificial intelligence.
Chih‐Kuan Yeh, Pradeep Ravikumar
doaj   +1 more source

A Novel Application of Ensemble Methods with Data Resampling Techniques for Drill Bit Selection in the Oil and Gas Industry

Energies, 2021
Selection of the most suitable drill bit type is an important task for drillers when planning for new oil and gas wells. With the advancement of intelligent predictive models, the automated selection of drill bit type is possible using earlier drilled ...
Saurabh Tewari, Umakant Dhar Dwivedi, Susham Biswas   +2 more
doaj   +1 more source

Tumor‐agnostic detection of circulating tumor DNA in patients with advanced pancreatic cancer using targeted DNA methylation sequencing and cell‐free DNA fragmentomics

Molecular Oncology, EarlyView.
We evaluated circulating tumor DNA (ctDNA) detection in advanced pancreatic cancer using DNA methylation, cell‐free DNA fragment lengths, and 5′ end motifs. Machine learning models were trained to estimate ctDNA levels from each feature and their combination.
Morten Lapin, Kjersti Tjensvoll, Karin Hestnes Edland, Satu Oltedal, Herish Garresori, Bjørnar Gilje, Saga Ekedal, Trygve Eftestøl, Jan Terje Kvaløy, Filip Janku, Oddmund Nordgård   +10 more
wiley   +1 more source

Monitoring the lactation-related behaviors of sows and their piglets in farrowing crates using deep learning

Frontiers in Animal Science
Pig farming is a major sector of livestock production. The preweaning stage is a critical period in the pig farming process, where lactation-related behaviors between sows and their piglets directly influence the preweaning survivability of the piglets ...
Yu-Jung Tsai, Yi-Che Huang, En-Chung Lin, Sheng-Chieh Lai, Xu-Chu Hong, Jonas Tsai, Cheng-En Chiang, Yan-Fu Kuo   +7 more
doaj   +1 more source