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- research-articleJanuary 2024
A Survey of Deep Learning for Detecting miRNA- Disease Associations: Databases, Computational Methods, Challenges, and Future Directions
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB), Volume 21, Issue 3Pages 328–347https://doi.org/10.1109/TCBB.2024.3351752MicroRNAs (miRNAs) are an important class of non-coding RNAs that play an essential role in the occurrence and development of various diseases. Identifying the potential miRNA-disease associations (MDAs) can be beneficial in understanding disease ...
- research-articleAugust 2023
scICML: Information-Theoretic Co-Clustering-Based Multi-View Learning for the Integrative Analysis of Single-Cell Multi-Omics Data
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB), Volume 21, Issue 1Pages 200–207https://doi.org/10.1109/TCBB.2023.3305989Modern high-throughput sequencing technologies have enabled us to profile multiple molecular modalities from the same single cell, providing unprecedented opportunities to assay cellular heterogeneity from multiple biological layers. However, the datasets ...
- research-articleJuly 2023
Network Biomarker Detection From Gene Co-Expression Network Using Gaussian Mixture Model Clustering
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB), Volume 20, Issue 6Pages 3523–3534https://doi.org/10.1109/TCBB.2023.3297388Finding network biomarkers from gene co-expression networks (GCNs) has attracted a lot of research interest. A network biomarker is a topological module, i.e., a group of densely connected nodes in a GCN, in which the gene expression values correlate with ...
- research-articleJuly 2023
MTGDC: A Multi-Scale Tensor Graph Diffusion Clustering for Single-Cell RNA Sequencing Data
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB), Volume 20, Issue 5Pages 3056–3067https://doi.org/10.1109/TCBB.2023.3293112Single-cell RNA sequencing (scRNA-seq) is a new technology that focuses on the expression levels for each cell to study cell heterogeneity. Thus, new computational methods matching scRNA-seq are designed to detect cell types among various cell groups. ...
- research-articleApril 2023
GCSTI: A Single-Cell Pseudotemporal Trajectory Inference Method Based on Graph Compression
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB), Volume 20, Issue 5Pages 2945–2958https://doi.org/10.1109/TCBB.2023.3266109The single-cell pseudotemporal trajectory inference is an important way to explore the process of developmental changes within a cell. Due to the uneven rate of cell growth, changes in gene expression depend less on the time of data collection and more on ...
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- research-articleMarch 2023
Self-Supervised Learning for Label Sparsity in Computational Drug Repositioning
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB), Volume 20, Issue 5Pages 3245–3256https://doi.org/10.1109/TCBB.2023.3254163The computational drug repositioning aims to discover new uses for marketed drugs, which can accelerate the drug development process and play an important role in the existing drug discovery system. However, the number of validated drug-disease ...
- research-articleJanuary 2023
ScCCL: Single-Cell Data Clustering Based on Self-Supervised Contrastive Learning
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB), Volume 20, Issue 3Pages 2233–2241https://doi.org/10.1109/TCBB.2023.3241129The growing maturity of single-cell RNA-sequencing (scRNA-seq) technology allows us to explore the heterogeneity of tissues, organisms, and complex diseases at cellular level. In single-cell data analysis, clustering calculation is very important. However,...
- research-articleJanuary 2023
NetPro: Neighborhood Interaction-Based Drug Repositioning via Label Propagation
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB), Volume 20, Issue 3Pages 2159–2169https://doi.org/10.1109/TCBB.2023.3234331Drug repositioning is an important approach for predicting new disease indications of the existing drugs in drug discovery. A great progress has been achieved in drug repositioning. However, effectively utilizing the localized neighborhood interaction ...
- opinionDecember 2022
Guest Editorial for Selected Papers From BIOKDD 2021
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB), Volume 19, Issue 6Pages 3068–3069https://doi.org/10.1109/TCBB.2022.3208759The papers in this special section were presented at the 20th International Workshop on Data Mining in Bioinformatics (BIOKDD 2021) that was held virtually on August 15, 2021. The conference featured the special theme of “Artificial Intelligence in ...
- opinionOctober 2022
Guest Editorial for Selected Papers From BIOKDD 2020
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB), Volume 19, Issue 5Pages 2545–2546https://doi.org/10.1109/TCBB.2022.3176912THE 19th International Workshop on Data Mining in Bioinformatics (BIOKDD 2020) was held virtually on August 24, 2020 due to the COVID-19 pandemic. BIOKDD 2020 featured the special theme of “Battling COVID-19” which particularly welcomed paper submissions ...
- research-articleJune 2022
Deep Transfer Learning for Communicable Disease Detection and Recommendation in Edge Networks
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB), Volume 20, Issue 4Pages 2468–2479https://doi.org/10.1109/TCBB.2022.3180393Considering the increasing number of communicable disease cases such as COVID-19 worldwide, the early detection of the disease can prevent and limit the outbreak. Besides that, the PCR test kits are not available in most parts of the world, and there is ...
- research-articleMay 2022
Layer-Specific Modules Detection in Cancer Multi-Layer Networks
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB), Volume 20, Issue 2Pages 1170–1179https://doi.org/10.1109/TCBB.2022.3176859Multi-layer networks provide an effective and efficient tool to model and characterize complex systems with multiple types of interactions, which differ greatly from the traditional single-layer networks. Graph clustering in multi-layer networks is highly ...
- research-articleMay 2022
Biomedical Argument Mining Based on Sequential Multi-Task Learning
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB), Volume 20, Issue 2Pages 864–874https://doi.org/10.1109/TCBB.2022.3173447Biomedical argument mining aims to automatically identify and extract the argumentative structure in biomedical text. It helps to determine not only what positions people adopt, but also why they hold such opinions, which provides valuable insights into ...
- research-articleMay 2022
LitMC-BERT: Transformer-Based Multi-Label Classification of Biomedical Literature With An Application on COVID-19 Literature Curation
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB), Volume 19, Issue 5Pages 2584–2595https://doi.org/10.1109/TCBB.2022.3173562The rapid growth of biomedical literature poses a significant challenge for curation and interpretation. This has become more evident during the COVID-19 pandemic. LitCovid, a literature database of COVID-19 related papers in PubMed, has accumulated over ...
- research-articleMay 2022
Predicting miRNA-Disease Associations via Node-Level Attention Graph Auto-Encoder
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB), Volume 20, Issue 2Pages 1308–1318https://doi.org/10.1109/TCBB.2022.3170843Previous studies have confirmed microRNA (miRNA), small single-stranded non-coding RNA, participates in various biological processes and plays vital roles in many complex human diseases. Therefore, developing an efficient method to infer potential miRNA ...
- research-articleJanuary 2022
MSF-LRR: Multi-Similarity Information Fusion Through Low-Rank Representation to Predict Disease-Associated Microbes
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB), Volume 20, Issue 1Pages 534–543https://doi.org/10.1109/TCBB.2022.3146176An Increase in microbial activity is shown to be intimately connected with the pathogenesis of diseases. Considering the expense of traditional verification methods, researchers are working to develop high-efficiency methods for detecting potential ...
- research-articleJanuary 2022
The Neural Metric Factorization for Computational Drug Repositioning
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB), Volume 20, Issue 1Pages 731–741https://doi.org/10.1109/TCBB.2022.3144429Computational drug repositioning aims to discover new therapeutic diseases for marketed drugs and has the advantages of low cost, short development cycle, and high controllability compared to traditional drug development. The matrix factorization model ...
- research-articleJanuary 2022
Multiview Robust Graph-Based Clustering for Cancer Subtype Identification
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB), Volume 20, Issue 1Pages 544–556https://doi.org/10.1109/TCBB.2022.3143897Cancer subtype identification is to classify cancer into groups according to their molecular characteristics and clinical manifestations and is the basis for more personalized diagnosis and therapy. Public datasets such as The Cancer Genome Atlas (TCGA) ...
- research-articleJanuary 2022
Inferring Latent MicroRNA-Disease Associations on a Gene-Mediated Tripartite Heterogeneous Multiplexing Network
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB), Volume 19, Issue 6Pages 3190–3201https://doi.org/10.1109/TCBB.2022.3143770MicroRNA (miRNA) is a class of non-coding single-stranded RNA molecules encoded by endogenous genes with a length of about 22 nucleotides. MiRNAs have been successfully identified as differentially expressed in various cancers. There is evidence that ...
- research-articleDecember 2021
Similarity Fusion via Exploiting High Order Proximity for Cancer Subtyping
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB), Volume 20, Issue 1Pages 658–667https://doi.org/10.1109/TCBB.2021.3139597Identifying cancer subtypes holds essential promise for improving prognosis and personalized treatment. Cancer subtyping based on multi-omics data has become a hotspot in bioinformatics research. One of the critical approaches of handling data ...