Article
Genetics & Heredity
Hui Min, Xiao-Hong Xin, Chu-Qiao Gao, Likun Wang, Pu-Feng Du
Summary: This study proposed a method named XGEM to predict essential miRNAs using the XGBoost framework with CART. XGEM showed promising prediction performance compared to other state-of-the-art methods, suggesting its potential in identifying essential miRNAs.
FRONTIERS IN GENETICS
(2022)
Article
Computer Science, Artificial Intelligence
Danyang Li, Zhuhong Zhang, Guihua Wen
Summary: Ensemble pruning improves system performance and reduces storage requirements in integration systems. Most approaches evaluate the competence and relationships of classifiers by analyzing their predictions to remove low-quality or redundant classifiers. However, finding the best way to represent classifiers and create ensemble diversity remains a research problem. To address this, we propose a new classifier selection method called CRCEEP, which incorporates two new classifier representation learning methods and a clustering ensemble method. Extensive experiments on UCI datasets demonstrate the effectiveness of CRCEEP and the importance of classifier representation.
APPLIED INTELLIGENCE
(2023)
Review
Cell Biology
Farbod Bahreini, Elham Rayzan, Nima Rezaei
Summary: Breast cancer, a multifactorial disease, may have an increased risk due to alterations in microRNA sequences. miR-SNPs are potential biomarkers for early detection of breast cancer.
JOURNAL OF CELLULAR PHYSIOLOGY
(2021)
Article
Oncology
Dengru Zheng, Ping Tang, Danping Lu, Liangfu Han, Sajjad Saberi
Summary: Machine learning approaches as intelligent medical assistants are not able to replace professional humans but can change the treatment of diseases like cancer. This paper proposes a new intelligent approach using feature selection and an optimized ensemble classifier for breast cancer diagnosis, which achieves better performance compared to existing algorithms.
JOURNAL OF CANCER RESEARCH AND CLINICAL ONCOLOGY
(2023)
Article
Plant Sciences
Haftom Brhane, Teklehaimanot Haileselassie, Kassahun Tesfaye, Cecilia Hammenhag, Rodomiro Ortiz, Kibrom B. Abreha, Mulatu Geleta
Summary: This study developed 13 new EST-SSR markers for assessing the genetic diversity of finger millet, as well as evaluated the genetic diversity of 55 landrace accessions and 5 cultivars in Ethiopia using 10 polymorphic SSR markers. The results showed a low genetic differentiation between accessions and geographic regions, indicating strong gene flow among finger millet populations.
FRONTIERS IN PLANT SCIENCE
(2021)
Article
Cell Biology
Concetta Scimone, Luigi Donato, Simona Alibrandi, Concetta Alafaci, Angela D'Ascola, Sergio Vinci, Rosalia D'Angelo, Antonina Sidoti
Summary: This study reveals the importance of epitranscriptomic modifications in gene expression regulation and suggests the involvement of altered epitranscriptome profile in the development of CCM. These findings provide new insights for further investigation into the pathogenesis of CCM.
AMERICAN JOURNAL OF PHYSIOLOGY-CELL PHYSIOLOGY
(2022)
Article
Biochemistry & Molecular Biology
Maria Radanova, Mariya Levkova, Galya Mihaylova, Rostislav Manev, Margarita Maneva, Rossen Hadgiev, Nikolay Conev, Ivan Donev
Summary: There is a growing interest in studying single nucleotide polymorphisms (SNPs) in microRNA (miRNA) genes, as they may be associated with susceptibility, prognosis, and treatment response in colorectal cancer (CRC). These miRNA-SNPs could serve as non-invasive biomarkers for early detection of CRC. However, contradictory findings have been reported when different research groups investigated the same SNP in a gene for a specific miRNA, highlighting the need for more case-control studies involving participants from different ethnic backgrounds. According to our review, three miRNA-SNPs - miR-146a rs2910164, miR-27a rs895819, and miR-608 rs4919510 - appear to be promising prognostic, diagnostic, and predictive biomarkers for CRC.
Article
Biochemistry & Molecular Biology
Fumie Takei, Misaki Akiyama, Minori Dateki
Summary: The study introduces a novel RT-Hpro-PCR technique for accurate detection of miRNAs with similar sequences. By enhancing the specificity of RT through the use of a DNA-tagged RT primer and hairpin probe structure, this method shows potential for exploring the roles of miRNAs in biological processes.
BIOORGANIC & MEDICINAL CHEMISTRY
(2021)
Article
Biochemical Research Methods
Mohammad Neamul Kabir, Limsoon Wong
Summary: This study presents a novel method called EnsembleFam that aims to improve function prediction for proteins in the twilight zone. By extracting core characteristics and using SVM classifiers, EnsembleFam achieves better accuracy in identifying proteins with low sequence homology compared to existing methods.
BMC BIOINFORMATICS
(2022)
Article
Biology
Fei Li, Shuai Liu, Kewei Li, Yaqi Zhang, Meiyu Duan, Zhaomin Yao, Gancheng Zhu, Yutong Guo, Ying Wang, Lan Huang, Fengfeng Zhou
Summary: DNA methylation is a major epigenetic modification that regulates biological processes without altering the DNA sequence. This study proposes a feature representation framework called EpiTEAmDNA, which integrates convolutional neural network and conventional machine learning methods. It shows improved performances compared to existing deep learning methods on small datasets across multiple DNA methylation types.
COMPUTERS IN BIOLOGY AND MEDICINE
(2023)
Article
Computer Science, Artificial Intelligence
Amgad M. Mohammed, Enrique Onieva, Michal Wozniak, Gonzalo Martinez-Munoz
Summary: This article discusses the strategy of classifier ensemble pruning, involving optimizing predefined performance criteria to identify subensembles. The study analyzes a set of heuristic metrics to guide the pruning process, with results indicating that ordered aggregation is an effective strategy for improving predictive performance and reducing computational complexities.
PATTERN RECOGNITION
(2022)
Review
Engineering, Environmental
Seyed Samad Hosseini, Asiyeh Jebelli, Somayeh Vandghanooni, Ali Jahanban-Esfahlan, Behzad Baradaran, Mohammad Amini, Negar Bidar, Miguel de la Guardia, Ahad Mokhtarzadeh, Morteza Eskandani
Summary: Single nucleotide polymorphisms (SNPs) are the main cause of individual variability and are associated with various diseases. The healthcare industry requires more advanced technologies to detect SNPs. This review focuses on novel SNP biosensors based on electrochemical, optical, and piezoelectric analysis, and explores future trends in sensing.
CHEMICAL ENGINEERING JOURNAL
(2022)
Article
Medicine, General & Internal
Maha Daghestani, Nashwa Othman, Mohammed A. Omair, Fahidah Alenzi, Maha A. Omair, Eman Alqurtas, Shireen Amin, Arjumand Warsy
Summary: This study conducted an investigation on the Saudi population and found that 6 single nucleotide polymorphisms (SNPs) were significantly associated with rheumatoid arthritis (RA), with 4 of them having a protective effect. Two SNPs showed significantly higher heterozygote frequencies in the control group compared to the patients. This indicates considerable heterogeneity in the genetics of RA in different populations.
JOURNAL OF CLINICAL MEDICINE
(2023)
Article
Chemistry, Analytical
Salvatore Petralia, Antonella Vigilanza, Emanuele Sciuto, Michele Maffia, Antonella Romanini, Sabrina Conoci
Summary: The study investigated single nucleotide polymorphisms in the MC1R gene using a miniaturized silicon-based microarray-chip, showing good sensitivity and high confidence level, paving the way for future development of portable genetic assays.
SENSORS AND ACTUATORS B-CHEMICAL
(2021)
Article
Medicine, Research & Experimental
Atsushi Yamaguchi, Yuto Mukai, Tomoya Sakuma, Yudai Suganuma, Ayako Furugen, Katsuya Narumi, Masaki Kobayashi
Summary: This study examined the influence of hMCT9 gene variants L93M and T258K on its transport characteristics. The results showed that L93M slightly decreased the transport activity of creatine, while T258K did not affect it. Interestingly, T258K abolished Na+ sensitivity and altered the substrate affinity.