A Monocyte-Driven Prognostic Model for Multiple Myeloma: Multi-Omics and Machine Learning Insights by Xie L, Gao M, Tan S, Zhou Y, Liu J, Wang L, Li X

“…Subsequently, based on 482 prognostic moDEGs, we developed and validated an optimal model, termed the Monocyte-related Gene Prognostic Signature (MGPS), by integrating 101 predictive models generated from 10 machine learning algorithms across multiple transcriptome sequencing datasets. …”
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Streamlining ICI Transformed as a Nonnegative System by David Hyland

“…The previous algorithm used initial conditions that were randomly assorted pixel intensities. …”
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Developing a novel aging assessment model to uncover heterogeneity in organ aging and screening of aging-related drugs by Yingqi Xu, Maohao Li, Congxue Hu, Yawen Luo, Xing Gao, Xinyu Li, Xia Li, Yunpeng Zhang

“…Furthermore, a random walk algorithm and a weighted integration approach combining gene set enrichment analysis were implemented to systematically screen potential drugs for mitigating multi-organ aging. …”
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Integrative analysis of bulk and single-cell transcriptomic data reveals novel insights into lipid metabolism and prognostic factors in hepatocellular carcinoma by Feiyu Qi, Guiming Zha, Yanfang Zhang, Sihua Liu, Yuhang Yang, Wanliang Sun, Dongdong Wang, Zhong Liu, Zheng Lu, Dengyong Zhang

“…Bulk transcriptomic and single-cell sequencing data for HCC were retrieved from public databases. …”
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Unravelling NK cell subset dynamics and specific gene signatures post-ibrutinib therapy in chronic lymphocytic leukaemia via single-cell transcriptomics by Chunlan Liu, Tianjian Ding, Rong Zou, Aili Zhang, Zhengzhuo Zhi, Sili Wang

“…Mendelian randomization analysis and colocalization analysis were employed to identify key genes. …”
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SCH-Hunter: A Taint-Based Hybrid Fuzzing Framework for Smart Contract Honeypots by Haoyu Zhang, Baotong Wang, Wenhao Fu, Leyi Shi

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Identification of PRKCQ-AS1 as a Keratinocyte-Derived Exosomal lncRNA That Promotes Th17 Differentiation and IL-17 secretion in Psoriasis Through Bioinformatics, Machine L... by Gao P, Gao X, Lin L, Zhang M, Luo D, Chen C, Li Y, He Y, Liu X, Shi C, Yang R

“…Subsequently, exosome-related ncRNAs in psoriasis lesions were identified primarily through weighted gene co-expression network analysis and five machine learning algorithms. Additionally, large-scale integrated single-cell RNA sequencing data and genome-wide association study (GWAS) data were included to investigate the mechanisms of key ncRNA, primarily through immune infiltration analysis, gene set enrichment analysis (GSEA), co-expression analysis, and Mendelian randomization. …”
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Exercise-changed gut mycobiome as a potential contributor to metabolic benefits in diabetes prevention: an integrative multi-omics study by Yao Wang, Jiarui Chen, Yueqiong Ni, Yan Liu, Xiang Gao, Michael Andrew Tse, Gianni Panagiotou, Aimin Xu

“…With our established randomized controlled trial of exercise intervention in Chinese males with prediabetes (n = 39, ClinicalTrials.gov:NCT03240978), we investigated the dynamics of human gut mycobiome and further interrogated their associations with exercise-elicited outcomes using multi-omics approaches.Methods Clinical variations and biological samples were collected before and after training. …”
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Short-term Wind Power Forecasting Based on BWO‒VMD and TCN‒BiGRU by LU Jing, ZHANG Yanru, WANG Rui

“…Compared to other optimization algorithms such as genetic algorithm (GA) and whale optimization algorithm (WOA), the BWO algorithm demonstrates significant per-formance, with faster running speed, stronger stability, and greater robustness. …”
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Pre-modulated multi-coset sampling system by Huang Zhen, Bai Zhengyao

“…Then, the modulated signal is sampled by the low-speed ADC, and each channel of low-speed ADC and random sequence generator share a same control clock. …”
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Investigating the Prognostic Role of Telomerase-Related Cellular Senescence Gene Signatures in Breast Cancer Using Machine Learning by Qiong Li, Hongde Liu

“…A comprehensive machine learning framework incorporating 101 algorithmic combinations across 10 survival modeling approaches, including random survival forests and ridge regression, was employed to develop a robust prognostic model. …”
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Enhanced Detection of Mitochondrial Heteroplasmy and DNA Hypomethylation in Adipose-Derived Mesenchymal Stem Cells Using a Novel Adaptive Sampling Protocol by Antonina Gospodinova, Yuliia Mariienko, Diana Pendicheva-Duhlenska, Soren Hayrabedyan, Krassimira Todorova

“…Our custom algorithm preserved phase relationships between base modifications and sequence polymorphisms. …”
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CYLD as a key regulator of myocardial infarction-to-heart failure transition revealed by multi-omics integration by Jingya Xu, Jingya Xu, Zhonghua Dong, Zhaodong Li, Xuan Wang, Xuan Wang

“…Our multistep analytical pipeline included weighted gene coexpression network analysis (WGCNA) to map interacting genes, machine learning algorithms for robust classification, functional annotation via Kyoto Encyclopedia of Genes and Genomes (KEGG) to explore biological pathways, CIBERSORT correlation analysis linking hub genes with immune cell states, transcriptional regulation profiling of key hubs, and single-cell sequencing to assess the functional relevance of these hubs.ResultsOur findings revealed that 413 DEGs were significantly different between MI and HF. …”
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Design of an Efficient Model for Psychological Disease Analysis and Prediction Using Machine Learning and Genomic Data Samples by Alparthi Kumuda, Saroj Kumar Panigrahy

“…The two central components of the PDMLG model include the Genomic Fusion Model, which uses ensemble learning techniques like Random Forest, Gradient Boosting, and Neural Networks, and Deep Learning Model of Convolutional and Recurrent Neural Networks in processing genomic sequence data samples. …”
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Digital Spectral Analysis by means of the Method of Averag Modified Periodograms Using Binary-Sign Stochastic Quantization of Signals by V. N. Yakimov

“…A special feature of this quantization is the use of a randomizing uniformly distributed auxiliary signal as a stochastic continuous quantization threshold (threshold function). …”
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SLC3A2 as a key anoikis−related gene for prognosis and tumor microenvironment remodeling in melanoma by Xiaojin Liu, Jiaheng Xie, Yingying Xiao

“…A total of 150 anoikis-related genes were identified, and 101 machine learning algorithms and their combinations (including Cox regression, random survival forest, and gradient boosting machine) were systematically evaluated to identify the optimal prognostic model. …”
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Identification of Key Modules of Lung Cancer in Gene Regulatory Network using Greedy Modularity Optimization Approach by Zahra Sadat Mirghadery, Mehrdad Kargari, Mostafa Akhavan-Safar

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The Equal-Time Waypoint Method: A Multi-AUV Path Planning Approach That Is Based on Velocity Variation by Chenxin Yin, Kai Shi, Hailong Wang

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Autonomic nervous system development-related signature as a novel predictive biomarker for immunotherapy in pan-cancers by Cunen Wu, Cunen Wu, Cunen Wu, Cunen Wu, Weiwei Xue, Yuwen Zhuang, Dayue Darrel Duan, Dayue Darrel Duan, Zhou Zhou, Zhou Zhou, Xiaoxiao Wang, Zhenfeng Wu, Jin-yong Zhou, Xiangkun Huan, Ruiping Wang, Haibo Cheng, Haibo Cheng

“…A pan-cancer predictive model for ICI prognosis based on ANSDR.Sig was constructed, with the random forest algorithm yielding the most robust performance. …”
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Specificity Analysis of Genome Based on Statistically Identical K-Words With Same Base Combination by Hyein Seo, Yong-Joon Song, Kiho Cho, Dong-Ho Cho

“…Finally, we propose a genetic algorithm-based search algorithm to select a minimum set of ratios useful for classification. …”
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