Results 101 to 110 of about 4,590,312 (339)

Analysing the significance of small conformational changes and low occupancy states in serial crystallographic data

FEBS Open Bio, EarlyView.
This protocol paper outlines methods to establish the success of a time‐resolved serial crystallographic experiment, by means of statistical analysis of timepoint data in reciprocal space and models in real space. We show how to amplify the signal from excited states to visualise structural changes in successful experiments.
Jake Hill, Yelyzaveta Pulnova, Elke De Zitter, Helen M. Ginn, Briony A. Yorke   +4 more
wiley   +1 more source

IA-KNNR: A Novel Imbalance-Aware Approach for Handling Multi-Label Class Imbalance Problem

IEEE Access
Multi-label learning (MLL) is a supervised learning where the classifier needs to learn from the data where one instance can belong to more than one class (label).
Himanshu Suyal, Shiv Naresh Shivhare, Gulshan Shrivastava, Rohit Singh, Ansh Singhal   +4 more
doaj   +1 more source

Classification with class imbalance problem: a review

, 2015
Most existing classification approaches assume the underlying training set is evenly distributed. In class imbalanced classification, the training set for one class (majority) far surpassed the training set of the other class (minority), in which, the ...
Ali, Aida, Ralescu, Anca L., Shamsuddin, Siti Mariyam   +2 more
core  

Evolutionarily divergent DUF4465 domains have a common vitamin B12‐binding function

FEBS Open Bio, EarlyView.
We show that DUF4465 family proteins, widespread across bacteria from gut microbiomes, hydrothermal vents, and soil, share a common vitamin B12‐binding function. These augmented β‐jellyroll proteins bind vitamin B12 via extended loops. Our findings establish sequence‐diverse DUF4465 proteins as a widespread class of B12‐binding proteins, highlighting ...
Charlea Clarke, Michal Banasik, Rokas Juodeikis, Martin J. Warren, Richard W. Pickersgill   +4 more
wiley   +1 more source

Implementasi Algoritma SMOTEBoost pada Kasus Imbalance Class [PDF]

, 2007
ABSTRAKSI: Imbalance class adalah ketidakseimbangan distribusi class label pada suatu data set. Dalam data mining berbagai penelitian telah dilakukan untuk mengatasi permasalahan imbalance class tersebut, salah satunya adalah algoritma SMOTEBoost ...
Ifa Saptina Rani
core  

Cyclic azapeptide CD36 ligand attenuates cardiac injury and reduces long‐chain fatty acid accumulation after myocardial ischemia–reperfusion in mice

FEBS Open Bio, EarlyView.
In a murine model of myocardial ischemia and reperfusion (MI/R), the CD36 azapeptide ligand MPE‐298 reduces cardiac injury and transiently lowers left ventricular long‐chain fatty acids (LCFAs) accumulation 3 h after reperfusion, accompanied by a decrease of oxidative stress and inflammation‐associated genes' expression in the heart and adipose tissue.
Jade Gauvin, Naghme Radmannia, David N. Huynh, Liliane Ménard, Caroline Daneault, Maïté Veilleux, Ahsanullah Ahsanullah, André C. Carpentier, William D. Lubell, Matthieu Ruiz, Huy Ong, Sylvie Marleau, Simon‐Pierre Gravel   +12 more
wiley   +1 more source

The impact of class imbalance in classification performance metrics based on the binary confusion matrix

Pattern Recognition, 2019
A major issue in the classification of class imbalanced datasets involves the determination of the most suitable performance metrics to be used. In previous work using several examples, it has been shown that imbalance can exert a major impact on the ...
Amalia Luque, A. Carrasco, Alejandro Martín, A. D. L. Heras   +3 more
semanticscholar   +1 more source

Misclassification analysis for the class imbalance problem

, 2010
In classification, the class imbalance issue normally causes the learning algorithm to be dominated by the majority classes and the features of the minority classes are sometimes ignored.
Wong, K.W., Fung, C.C., Takama, Y., Jeatrakul, P.   +3 more
core  

A Method for Class-Imbalance Learning in Android Malware Detection

, 2021
More and more Android application developers are adopting many different methods against reverse engineering, such as adding a shell, resulting in certain features that cannot be obtained through decompilation, which causes a serious sample imbalance in ...
Jun Guan, Xu Jiang, Baolei Mao
core   +1 more source

Hybrid approach redefinition with progressive boosting for class imbalance problem [PDF]

, 2020
Problems of Class Imbalance in data classification have received attention from many researchers. It is because the imbalance class will affect the accuracy of the classification results. The problem of the imbalance class itself will ignore the minority
Hartono, Hartono, Ongko, Erianto
core   +1 more source