Results 101 to 110 of about 1,682,433 (269)

Comparison of linear and non-linear machine learning models for time-dependent readmission or mortality prediction among hospitalized heart failure patients. [PDF]

Heliyon, 2023
Tong R, Zhu Z, Ling J.
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

Non-linear machine learning models incorporating SNPs and PRS improve polygenic prediction in diverse human populations. [PDF]

Commun Biol, 2022
Elgart M, Lyons G, Romero-Brufau S, Kurniansyah N, Brody JA, Guo X, Lin HJ, Raffield L, Gao Y, Chen H, de Vries P, Lloyd-Jones DM, Lange LA, Peloso GM, Fornage M, Rotter JI, Rich SS, Morrison AC, Psaty BM, Levy D, Redline S, NHLBI’s Trans-Omics in Precision Medicine (TOPMed) Consortium, Sofer T.   +22 more
europepmc   +1 more source

Genetic attenuation of ALDH1A1 increases metastatic potential and aggressiveness in colorectal cancer

Molecular Oncology, EarlyView.
Aldehyde dehydrogenase 1A1 (ALDH1A1) is a cancer stem cell marker in several malignancies. We established a novel epithelial cell line from rectal adenocarcinoma with unique overexpression of this enzyme. Genetic attenuation of ALDH1A1 led to increased invasive capacity and metastatic potential, the inhibition of proliferation activity, and ultimately ...
Martina Poturnajova, Zuzana Kozovska, Ondrej Pos, Kristina Pavlov, Sachin Gulati, Peter Makovicky, Kristina Jakic, Monika Burikova, Eva Sedlackova, Barbora Svitkova, Silvia Tyciakova, Vojtech Bystry, Nicolas Blavet, Boris Tichy, Matej Hrnciar, Jaroslav Budis, Miroslav Tomas, Peter Dubovan, Georgina Kolnikova, Veronika Repaska, Nikoleta Mojzesova, Eva Zomborska, Daniel Pindak, Michal Mego, Tomas Szemes, Miroslava Matuskova   +25 more
wiley   +1 more source

Efficiency of the Adjusted Binary Classification (ABC) Approach in Osteometric Sex Estimation: A Comparative Study of Different Linear Machine Learning Algorithms and Training Sample Sizes. [PDF]

Biology (Basel), 2022
Attia MH, Kholief MA, Zaghloul NM, Kružić I, Anđelinović Š, Bašić Ž, Jerković I.   +6 more
europepmc   +1 more source

Rethinking plastic waste: innovations in enzymatic breakdown of oil‐based polyesters and bioplastics

FEBS Open Bio, EarlyView.
Plastic pollution remains a critical environmental challenge, and current mechanical and chemical recycling methods are insufficient to achieve a fully circular economy. This review highlights recent breakthroughs in the enzymatic depolymerization of both oil‐derived polyesters and bioplastics, including high‐throughput protein engineering, de novo ...
Elena Rosini, Nicolò Antonelli, Gianluca Molla   +2 more
wiley   +1 more source

Using neuroimaging to predict relapse in stimulant dependence: A comparison of linear and machine learning models

NeuroImage: Clinical, 2019
Objective: Relapse rates are consistently high for stimulant user disorders. In order to obtain prognostic information about individuals in treatment, machine learning models have been applied to neuroimaging and clinical data.
Joshua L. Gowin, Monique Ernst, Tali Ball, April C. May, Matthew E. Sloan, Susan F. Tapert, Martin P. Paulus   +6 more
doaj   +1 more source

Identification of an epigenetic signature in human induced pluripotent stem cells using a linear machine learning model. [PDF]

Hum Cell, 2021
Nishino K, Takasawa K, Okamura K, Arai Y, Sekiya A, Akutsu H, Umezawa A.   +6 more
europepmc   +1 more source

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

FEBS 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, Sylvia Vagena, Pavlos Pantelis, Giorgos Theocharous, Russel Petty, Konstantinos Evangelou, Vassilis G. Gorgoulis   +6 more
wiley   +1 more source

Development of a new flux switching transverse flux machine with the ability of linear motion

CES Transactions on Electrical Machines and Systems, 2018
This paper proposes a new rotary flux switching transverse flux machine with the ability of linear motion (FSTFMaLM), in which both the stator and the rotor cores are made by using soft magnetic composite (SMC) materials. With the special design pattern,
Chengcheng Liu, Shaopeng Wang, Youhua Wang, Gang Lei, Youguang Guo, Jianguo Zhu   +5 more
doaj   +1 more source