Generalized Low-Rank Plus Sparse Tensor Estimation by Fast Riemannian Optimization by Jian-Feng Cai (498405)

Binary contingency table. by Lu Xiao (314030)

Overview of the segmentation algorithm. by Michael C. Robitaille (11949174)

RMSE on the test data when fitting (logistic) quadratic models to binary data across increasing measurement error values . by Jakub Stoklosa (3315042)

Secure MANET routing with blockchain-enhanced latent encoder coupled GANs and BEPO optimization by Sandeep Jagonda Patil (22048337)

“…By integrating Latent Encoder Coupled Generative Adversarial Network (LEGAN) optimized with Binary Emperor Penguin optimizer (BEPO), the scheme enhances routing efficiency and security. …”

The Pseudo-Code of the IRBMO Algorithm. by Chenyi Zhu (9383370)

“…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …”

DataSheet1_Optimal Sparsity Selection Based on an Information Criterion for Accurate Gene Regulatory Network Inference.PDF by Deniz Seçilmiş (13028616)

DataSheet1_Optimal Sparsity Selection Based on an Information Criterion for Accurate Gene Regulatory Network Inference.PDF by Deniz Seçilmiş (13028616)

IRBMO vs. meta-heuristic algorithms boxplot. by Chenyi Zhu (9383370)

“…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …”

IRBMO vs. feature selection algorithm boxplot. by Chenyi Zhu (9383370)

“…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …”

LASSO-Cox Regression Analysis to Screen Prognosis-Related Genes. by Jie Chu (293795)

QSAR model for predicting neuraminidase inhibitors of influenza A viruses (H1N1) based on adaptive grasshopper optimization algorithm by Z.Y. Algamal (5547620)

“…Obtaining a reliable QSAR model with few descriptors is an essential procedure in chemometrics. The binary grasshopper optimization algorithm (BGOA) is a new meta-heuristic optimization algorithm, which has been used successfully to perform feature selection. …”

Inferring Gene Regulatory Networks Using the Improved Markov Blanket Discovery Algorithm by Interdis Sci Comp Life Sci (7335308)

“…<ul><li><a href="https://link.springer.com/article/10.1007/s12539-021-00478-9#auth-Wei-Liu-Aff1-Aff2" target="_blank">Wei Liu</a>, </li><li><a href="https://link.springer.com/article/10.1007/s12539-021-00478-9#auth-Yi-Jiang-Aff1" target="_blank">Yi Jiang</a>, </li><li><a href="https://link.springer.com/article/10.1007/s12539-021-00478-9#auth-Li-Peng-Aff3" target="_blank">Li Peng</a>, </li><li><a href="https://link.springer.com/article/10.1007/s12539-021-00478-9#auth-Xingen-Sun-Aff1" target="_blank">Xingen Sun</a>, </li><li><a href="https://link.springer.com/article/10.1007/s12539-021-00478-9#auth-Wenqing-Gan-Aff1" target="_blank">Wenqing Gan</a>, </li><li><a href="https://link.springer.com/article/10.1007/s12539-021-00478-9#auth-Qi-Zhao-Aff4" target="_blank">Qi Zhao</a>,</li><li><a href="https://link.springer.com/article/10.1007/s12539-021-00478-9#auth-Huanrong-Tang-Aff1" target="_blank">Huanrong Tang</a></li></ul><p dir="ltr">A novel network inference method based on the improved MB discovery algorithm, IMBDANET, was proposed for improving gene regulatory networks. …”

Inferring Gene Regulatory Networks Using the Improved Markov Blanket Discovery Algorithm by Interdis Sci Comp Life Sci (7335308)

“…<ul><li><a href="https://link.springer.com/article/10.1007/s12539-021-00478-9#auth-Wei-Liu-Aff1-Aff2" target="_blank">Wei Liu</a>, </li><li><a href="https://link.springer.com/article/10.1007/s12539-021-00478-9#auth-Yi-Jiang-Aff1" target="_blank">Yi Jiang</a>, </li><li><a href="https://link.springer.com/article/10.1007/s12539-021-00478-9#auth-Li-Peng-Aff3" target="_blank">Li Peng</a>, </li><li><a href="https://link.springer.com/article/10.1007/s12539-021-00478-9#auth-Xingen-Sun-Aff1" target="_blank">Xingen Sun</a>, </li><li><a href="https://link.springer.com/article/10.1007/s12539-021-00478-9#auth-Wenqing-Gan-Aff1" target="_blank">Wenqing Gan</a>, </li><li><a href="https://link.springer.com/article/10.1007/s12539-021-00478-9#auth-Qi-Zhao-Aff4" target="_blank">Qi Zhao</a> </li><li><a href="https://link.springer.com/article/10.1007/s12539-021-00478-9#auth-Huanrong-Tang-Aff1" target="_blank">Huanrong Tang</a></li></ul><p dir="ltr">A novel network inference method based on the improved MB discovery algorithm, IMBDANET, was proposed for improving gene regulatory networks. …”

Symmetry test result. by Jiyong Moon (16819302)

Data_Sheet_1_Crystal Structure Prediction of Binary Alloys via Deep Potential.PDF by Haidi Wang (9694004)

Predicting Thermal Decomposition Temperature of Binary Imidazolium Ionic Liquid Mixtures from Molecular Structures by Hongpeng He (348094)

“…The subset of optimal descriptors was screened by combining the genetic algorithm with the multiple linear regression method. …”

Table 1_Identification of a signature gene set for oxaliplatin sensitivity prediction in colorectal cancer.xlsx by Xiaopeng Zhan (4170574)

“…Machine learning algorithms to these datasets was applied to identify genes associated with oxaliplatin response. …”

Image 1_Identification of a signature gene set for oxaliplatin sensitivity prediction in colorectal cancer.pdf by Xiaopeng Zhan (4170574)

“…Machine learning algorithms to these datasets was applied to identify genes associated with oxaliplatin response. …”

Data Sheet 4_Identification of a signature gene set for oxaliplatin sensitivity prediction in colorectal cancer.pdf by Xiaopeng Zhan (4170574)

“…Machine learning algorithms to these datasets was applied to identify genes associated with oxaliplatin response. …”