Results 181 to 190 of about 86,959 (305)

PanForest: predicting genes in genomes using random forests. [PDF]

Bioinformatics
Beavan AJS, Domingo-Sananes MR, McInerney JO.   +2 more
europepmc   +1 more source

Understory restoration in Hamilton urban forests

, 2011
Research was undertaken to determine how the understory vegetation of Hamilton urban forests compares with reference old-growth forests in rural locations, identify causes for differences, and develop methods to enhance species diversity.
Miller, Kieran Troy
core  

Enzymatic DNA Reaction Networks for Orchestrating Stimuli‐Dependent Temporal Molecular Pulse

Advanced Science, EarlyView.
We present an enzymatic DNA reaction network (EDRN) that encodes nucleic‐acid targets in time, converting inputs into a universal strand and then into programmable transient fluorescence pulses. With time‐color multiplexing, EDRN enables single‐tube high‐plex nucleic acid detection and shows strong agreement with clinical sequencing across 32 specimens.
Jiayu Yang, Yali Chang, Zibin Chu, Linghao Zhang, Tengfang Zhang, Dai Erhei, Xin Su, Zhe Yin   +7 more
wiley   +1 more source

Indirect state-level estimation of sexual minority adolescent populations by sex, age, and race/ethnicity using random forests. [PDF]

PLoS One
Alves-Maciel B, Pampati S, Fodeman A, Van Handel M, Zheng L, Ye Z, Yaesoubi R, Salomon JA.   +7 more
europepmc   +1 more source

Cuproptosis and Mitophagy Mediated by the THUMPD1/IGF2R‐Dependent Suppression of AKT and Activation of AMPK Signaling Suppress Lung Adenocarcinoma Progression

Advanced Science, EarlyView.
THUMPD1 drives a tumor‐suppressive signaling cascade in lung adenocarcinoma by promoting IGF2R expression. IGF2R associates with PPP2R1A to suppress AKT and activate AMPK, leading to SLC31A1 upregulation and copper accumulation. Elevated copper disrupts mitochondrial metabolism and induces excessive mitophagy, thereby restraining tumor growth and ...
Kai Wu, Bo Qin, Zhuoyu Gu, Weizheng Ding, Xiaoming Chen, Kaishang Zhang, Yujin Qiao, Shuang Yuan, Song Zhao, Xiangnan Li, Peng Zhang   +10 more
wiley   +1 more source

Determining the relative importance of risk and protective factors for adjustment disorder symptoms during the COVID-19 pandemic by mixed-effects random forests. [PDF]

Psychol Med
Lotzin A, Finne E, Schildbach G, Acquarini E, Ajdukovic D, Ajdukovic M, Anastassiou-Hadjicharalambous X, Ardino V, Hensler I, Arnberg FK, Böttche M, Dragan M, Figueiredo-Braga M, Gelezelyte O, Grajewski P, Groen S, van Hoof MJ, Javakhishvili JD, Kazlauskas E, Lioupi C, Lueger-Schuster B, Sales L, Tsiskarishvili L, Zrnic Novakovic I, Schäfer I, ADJUST Study Consortium.   +25 more
europepmc   +1 more source

EFFNet: A skin cancer classification model based on feature fusion and random forests. [PDF]

PLoS One, 2023
Ma X, Shan J, Ning F, Li W, Li H.
europepmc   +1 more source

An Integrated NLP‐ML Framework for Property Prediction and Design of Steels

Advanced Science, EarlyView.
This study presents a data‐driven framework that uses language‐processing techniques to interpret steel processing descriptions and machine‐learning models to predict mechanical properties. By organising complex process histories into meaningful groups and enabling rapid property forecasts, the work supports faster, more informed steel design through ...
Kiran Devraju, Adithya Umanath Rai, Jose Thomson, Marzie Ghorbani, Shujing Zhao, Nick Birbilis   +5 more
wiley   +1 more source

Retraction Note: Optimizing credit card fraud detection with random forests and SMOTE. [PDF]

Sci Rep
Sundaravadivel P, Isaac RA, Elangovan D, KrishnaRaj D, Rahul VVL, Raja R.   +5 more
europepmc   +1 more source

Consistency of Online Random Forests

, 2013
As a testament to their success, the theory of random forests has long been outpaced by their application in practice. In this paper, we take a step towards narrowing this gap by providing a consistency result for online random ...
Nando De Freitas, de Freitas, Nando, Misha Denil, Denil, Misha, Matheson, David, David Matheson   +5 more
core