Decoding dynamic miRNA:ceRNA interactions unveils therapeutic insights and targets across predominant cancer landscapes
Competing endogenous RNAs play key roles in cellular molecular mechanisms through cross-talk in post-transcriptional interactions. Studies on ceRNA cross-talk, which is particularly dependent on the abundance ... (Source: BioData Mining)
Source: BioData Mining - April 17, 2024 Category: Bioinformatics Authors: Selcen Ari Yuka and Alper Yilmaz Tags: Research Source Type: research
Evaluation of network-guided random forest for disease gene discovery
Gene network information is believed to be beneficial for disease module and pathway identification, but has not been explicitly utilized in the standard random forest (RF) algorithm for gene expression data a... (Source: BioData Mining)
Source: BioData Mining - April 16, 2024 Category: Bioinformatics Authors: Jianchang Hu and Silke Szymczak Tags: Research Source Type: research
MOCAT: multi-omics integration with auxiliary classifiers enhanced autoencoder
Integrating multi-omics data is emerging as a critical approach in enhancing our understanding of complex diseases. Innovative computational methods capable of managing high-dimensional and heterogeneous datas... (Source: BioData Mining)
Source: BioData Mining - March 5, 2024 Category: Bioinformatics Authors: Xiaohui Yao, Xiaohan Jiang, Haoran Luo, Hong Liang, Xiufen Ye, Yanhui Wei and Shan Cong Tags: Research Source Type: research
Interpreting drug synergy in breast cancer with deep learning using target-protein inhibition profiles
Breast cancer is the most common malignancy among women worldwide. Despite advances in treating breast cancer over the past decades, drug resistance and adverse effects remain challenging. Recent therapeutic p... (Source: BioData Mining)
Source: BioData Mining - February 29, 2024 Category: Bioinformatics Authors: Thanyawee Srithanyarat, Kittisak Taoma, Thana Sutthibutpong, Marasri Ruengjitchatchawalya, Monrudee Liangruksa and Teeraphan Laomettachit Tags: Research Source Type: research
Interaction models matter: an efficient, flexible computational framework for model-specific investigation of epistasis
Epistasis, the interaction between two or more genes, is integral to the study of genetics and is present throughout nature. Yet, it is seldom fully explored as most approaches primarily focus on single-locus ... (Source: BioData Mining)
Source: BioData Mining - February 28, 2024 Category: Bioinformatics Authors: Sandra Batista, Vered Senderovich Madar, Philip J. Freda, Priyanka Bhandary, Attri Ghosh, Nicholas Matsumoto, Apurva S. Chitre, Abraham A. Palmer and Jason H. Moore Tags: Methodology Source Type: research
Assessment of the causal relationship between gut microbiota and cardiovascular diseases: a bidirectional Mendelian randomization analysis
This study aims to elucidate the causal relati... (Source: BioData Mining)
Source: BioData Mining - February 26, 2024 Category: Bioinformatics Authors: Xiao-Ce Dai, Yi Yu, Si-Yu Zhou, Shuo Yu, Mei-Xiang Xiang and Hong Ma Tags: Research Source Type: research
A network-based drug prioritization and combination analysis for the MEK5/ERK5 pathway in breast cancer
Prioritizing candidate drugs based on genome-wide expression data is an emerging approach in systems pharmacology due to its holistic perspective for preclinical drug evaluation. In the current study, a networ... (Source: BioData Mining)
Source: BioData Mining - February 21, 2024 Category: Bioinformatics Authors: Regan Odongo, Asuman Demiroglu-Zergeroglu and Tunahan Çakır Tags: Research Source Type: research
m1A-Ensem: accurate identification of 1-methyladenosine sites through ensemble models
1-methyladenosine (m1A) is a variant of methyladenosine that holds a methyl substituent in the 1st position having a prominent role in RNA stability and human metabolites. (Source: BioData Mining)
Source: BioData Mining - February 15, 2024 Category: Bioinformatics Authors: Muhammad Taseer Suleman, Fahad Alturise, Tamim Alkhalifah and Yaser Daanial Khan Tags: Research Source Type: research
Revealing third-order interactions through the integration of machine learning and entropy methods in genomic studies
Non-linear relationships at the genotype level are essential in understanding the genetic interactions of complex disease traits. Genome-wide association Studies (GWAS) have revealed statistical association of... (Source: BioData Mining)
Source: BioData Mining - January 30, 2024 Category: Bioinformatics Authors: Burcu Yald ız, Onur Erdoğan, Sevda Rafatov, Cem Iyigün and Yeşim Aydın Son Tags: Research Source Type: research
Antibody selection strategies and their impact in predicting clinical malaria based on multi-sera data
Nowadays, the chance of discovering the best antibody candidates for predicting clinical malaria has notably increased due to the availability of multi-sera data. The analysis of these data is typically divide... (Source: BioData Mining)
Source: BioData Mining - January 25, 2024 Category: Bioinformatics Authors: Andr é Fonseca, Mikolaj Spytek, Przemysław Biecek, Clara Cordeiro and Nuno Sepúlveda Tags: Research Source Type: research
Machine learning approaches to identify systemic lupus erythematosus in anti-nuclear antibody-positive patients using genomic data and electronic health records
Although the 2019 EULAR/ACR classification criteria for systemic lupus erythematosus (SLE) has required at least a positive anti-nuclear antibody (ANA) titer ( ≥ 1:80), it remains challenging for clinicians to ... (Source: BioData Mining)
Source: BioData Mining - January 5, 2024 Category: Bioinformatics Authors: Chih-Wei Chung, Seng-Cho Chou, Tzu-Hung Hsiao, Grace Joyce Zhang, Yu-Fang Chung and Yi-Ming Chen Tags: Research Source Type: research
Optimizing age-related hearing risk predictions: an advanced machine learning integration with HHIE-S
The elderly are disproportionately affected by age-related hearing loss (ARHL). Despite being a well-known tool for ARHL evaluation, the Hearing Handicap Inventory for the Elderly Screening version (HHIE-S) ha... (Source: BioData Mining)
Source: BioData Mining - December 14, 2023 Category: Bioinformatics Authors: Tzong-Hann Yang, Yu-Fu Chen, Yen-Fu Cheng, Jue-Ni Huang, Chuan-Song Wu and Yuan-Chia Chu Tags: Research Source Type: research
6mA-StackingCV: an improved stacking ensemble model for predicting DNA N6-methyladenine site
DNA N6-adenine methylation (N6-methyladenine, 6mA) plays a key regulating role in the cellular processes. Precisely recognizing 6mA sites is of importance to further explore its biological functions. Although ... (Source: BioData Mining)
Source: BioData Mining - November 27, 2023 Category: Bioinformatics Authors: Guohua Huang, Xiaohong Huang and Wei Luo Tags: Methodology Source Type: research
Endoscopy-based IBD identification by a quantized deep learning pipeline
Discrimination between patients affected by inflammatory bowel diseases and healthy controls on the basis of endoscopic imaging is an challenging problem for machine learning models. Such task is used here as ... (Source: BioData Mining)
Source: BioData Mining - November 25, 2023 Category: Bioinformatics Authors: Massimiliano Datres, Elisa Paolazzi, Marco Chierici, Matteo Pozzi, Antonio Colangelo, Marcello Dorian Donzella and Giuseppe Jurman Tags: Methodology Source Type: research
DeepAutoGlioma: a deep learning autoencoder-based multi-omics data integration and classification tools for glioma subtyping
The classification of glioma subtypes is essential for precision therapy. Due to the heterogeneity of gliomas, the subtype-specific molecular pattern can be captured by integrating and analyzing high-throughpu... (Source: BioData Mining)
Source: BioData Mining - November 15, 2023 Category: Bioinformatics Authors: Sana Munquad and Asim Bikas Das Tags: Research Source Type: research
