Review
Cell Biology
Lingfeng Li, Xu Zhang, Nian Liu, Xiang Chen, Cong Peng
Summary: LINC00473, an oncogenic lncRNA, is upregulated in various human malignancies and associated with poor clinical outcomes. Its overexpression can promote cell proliferation, migration, and invasion, suggesting it as a potential prognostic biomarker and therapeutic target for human cancers.
JOURNAL OF CELLULAR PHYSIOLOGY
(2021)
Article
Biochemistry & Molecular Biology
Zoe Ward, Sebastian Schmeier, Louis Saddic, Martin Sigurdsson, Vicky A. Cameron, John Pearson, Allison Miller, Arthur Morley-Bunker, Josh Gorham, Jonathan G. Seidman, Christine S. Moravec, Wendy E. Sweet, Sary F. Aranki, Simon Body, Jochen D. Muehlschlegel, Anna P. Pilbrow
Summary: The study identified several novel lncRNAs associated with early response to ischemia in the heart, suggesting that one of these lncRNAs may serve as a potential therapeutic target or early marker for myocardial dysfunction.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2021)
Article
Biochemistry & Molecular Biology
Sonia Garcia-Ruiz, Emil K. Gustavsson, David Zhang, Regina H. Reynolds, Zhongbo Chen, Aine Fairbrother-Browne, Ana Luisa Gil-Martinez, Juan A. Botia, Leonardo Collado-Torres, Mina Ryten
Summary: Dysregulation of RNA splicing is implicated in rare and complex diseases. We have developed IntroVerse, a comprehensive resource for exploring intron usage by providing a catalogue of annotated introns and novel junctions. This dataset, generated from extensive RNA sequencing analysis, offers insights into novel transcripts and assessment of splicing noise in introns.
NUCLEIC ACIDS RESEARCH
(2023)
Article
Biochemistry & Molecular Biology
Makoto Arai, Hiroki Ochi, Satoko Sunamura, Nobuaki Ito, Masaomi Nangaku, Shu Takeda, Shingo Sato
Summary: This study identified a novel osteocyte-specific long noncoding RNA (lncRNA953Rik) that suppresses osteogenic differentiation by inhibiting the Wnt/beta-catenin signaling pathway. This research clarifies the role of lncRNAs in osteocytes for the first time and provides new therapeutic options for bone metabolic diseases such as osteoporosis.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2023)
Article
Medicine, Research & Experimental
Yueying Chen, HanyangLi Li, Lijie Lai, Yong Huang, Jun Shen
Summary: This study proposes a novel method based on cDNA microarray data to identify the potential function of evolutionarily conserved lncRNAs in UC. By analyzing over 12,000 microarray probes, the study found distinct expression patterns of lncRNAs in patients with UC and validated these findings through experimental validation. The study highlights the potential role of lncRNAs in the pathogenesis of UC.
Review
Pharmacology & Pharmacy
Hyunjong Kim, Jaesub Kim, Juhee Ryu
Summary: Retinopathy of prematurity (ROP) is a vascular disease that has become a primary cause of blindness in children worldwide. Although current therapies such as laser therapy and pharmacologic agents are commonly used to treat ROP, the search for novel therapeutic targets with less destructive properties is necessary. Noncoding RNA therapy has shown potential as next-generation therapy for treating ROP by regulating various noncoding RNAs.
FRONTIERS IN PHARMACOLOGY
(2022)
Review
Cell Biology
Anuradha Kirtonia, Milad Ashrafizadeh, Ali Zarrabi, Kiavash Hushmandi, Amirhossein Zabolian, Atefe K. Bejandi, Reshma Rani, Amit K. Pandey, Prakash Baligar, Vinit Kumar, Bhudev C. Das, Manoj Garg
Summary: Acute myeloid leukemia (AML) is a hematological disorder characterized by blocked myeloid differentiation and increased immature myeloid progenitors. Long noncoding RNAs (lncRNAs) are considered potential diagnostic, therapeutic, and prognostic factors in AML, with altered expression playing a significant role in leukemic transformation and involvement in various molecular pathways.
JOURNAL OF CELLULAR PHYSIOLOGY
(2022)
Article
Cell Biology
Guanzhi Liu, Sen Luo, Yutian Lei, Ming Jiao, Ruomu Cao, Huanshuai Guan, Run Tian, Kunzheng Wang, Pei Yang
Summary: Using high-throughput RNA sequencing, we identified differentially expressed lncRNA and genes in patients with ONFH and femoral neck fractures. lncRNA GAS5 is associated with BMSC osteogenic differentiation and is downregulated in both ONFH patients and ONFH rat models.
FRONTIERS IN CELL AND DEVELOPMENTAL BIOLOGY
(2022)
Article
Cardiac & Cardiovascular Systems
Wei Zhang, Jinjing Zhao, Lin Deng, Nestor Ishimwe, Jessica Pauli, Wen Wu, Shengshuai Shan, Wolfgang Kempf, Margaret D. Ballantyne, David Kim, Qing Lyu, Matthew Bennett, Julie Rodor, Adam W. Turner, Yao Wei Lu, Ping Gao, Mihyun Choi, Ganesh Warthi, Ha Won Kim, Margarida M. Barroso, William B. Bryant, Clint L. Miller, Neal L. Weintraub, Lars Maegdefessel, Joseph M. Miano, Andrew H. Baker, Xiaochun Long
Summary: The study discovered that INKILN is involved in the regulation of vascular smooth muscle cell (VSMC) inflammation and plays a role in the development of atherosclerosis and abdominal aortic aneurysm. INKILN activates the expression of inflammatory genes through interaction with MKL1 in VSMCs. This study provides a novel and physiologically relevant approach for investigating human-specific long noncoding RNAs under vascular disease conditions.
Article
Cell Biology
Hossein Sadeghi, Ehsan Nazemalhosseini-Mojarad, Unes Sahebi, Elnaz Fazeli, Ghasem Azizi-Tabesh, Vahid R. Yassaee, Sanaz Savabkar, Hamid Asadzadeh Aghdaei, Mohammad R. Zali, Reza Mirfakhraie
Summary: Vitamin D treatment modulates the expression of CYP24A1, PFDN4, and certain lncRNAs in colorectal cancer cells, which show potential as diagnostic biomarkers for colorectal cancer. The study suggests a cell-specific regulation of gene expression by vitamin D.
JOURNAL OF CELLULAR PHYSIOLOGY
(2021)
Review
Virology
Sasidharanpillai Sabeena
Summary: This review discusses the role of noncoding RNAs as diagnostic and prognostic biomarkers in cervical cancer. The existing studies on microRNA signatures in body fluids and cervical cancer tissues lack consistency and lack validated assays. The precise evaluation of immune-associated long noncoding RNA signatures in clinical samples is necessary. Research on the safe delivery methods, toxicities, and side effects of lncRNAs to tumor tissues is needed. Prospective studies on the diagnostic and prognostic roles of circulating lncRNAs and Piwil RNAs in cervical cancer cases are crucial. Comprehensive research is required for the clinical application of lncRNA-based biomarkers, as the impact of noncoding transcripts on molecular pathways is complex. Standardization and validation of deregulated ncRNAs in noninvasive samples of cervical cancer cases are essential.
JOURNAL OF MEDICAL VIROLOGY
(2023)
Article
Medicine, Research & Experimental
Di Lei, Congcong Fang, Na Deng, Baozhen Yao, Cuifang Fan
Summary: This study identified differential expression of multiple lncRNAs and mRNAs in placental samples of patients with early onset severe preeclampsia (EOSP). The upregulation of lncRNA Mir210HG in PE placentas suggests its potential role as a pathogenic marker, associated with the canonical Wnt signaling pathway. Overexpression of MiR210HG was found to affect trophoblast migration and invasion by targeting the miR-520a-3p/Dickkopf-1 axis in HTR-8/SVneo cells.
Article
Cell & Tissue Engineering
Fuquan Chen, Miao Zhang, Xiao Feng, Xiaomin Li, Haotian Sun, Xinyi Lu
Summary: A novel long noncoding RNA (lncRNA) Lx8-SINE B2 was identified as a marker of pluripotency in embryonic stem cells (ESCs), enriched in ESCs and driven by core pluripotency regulators Oct4 and Sox2.
STEM CELLS INTERNATIONAL
(2021)
Article
Multidisciplinary Sciences
Weidun Xie, Xingjian Chen, Zetian Zheng, Fuzhou Wang, Xiaowei Zhu, Qiuzhen Lin, Yanni Sun, Ka-Chun Wong
Summary: This study presents a method called lncRNA-Top to predict lncRNA-gene regulation relationships and constructs controlled deep-learning models. Through case studies, it is found that the predictions are accurate, and additional software is provided for target candidate annotation.
Article
Medicine, Research & Experimental
Yumin Zhu, Siqi Wang, Xiaochen Xi, Minfeng Zhang, Xiaofan Liu, Weina Tang, Peng Cai, Shaozhen Xing, Pengfei Bao, Yunfan Jin, Weihao Zhao, Yinghui Chen, Huanan Zhao, Xiaodong Jia, Shanshan Lu, Yinying Lu, Lei Chen, Jianhua Yin, Zhi John Lu
Summary: The study utilized sequencing technologies to detect different types of cancer-related RNA variations in plasma, revealing pathways associated with tumorigenesis and metastasis, immune responses, and metabolism. A 3-RNA detection panel for liver cancer was identified, showing promise for detecting AFP-negative and early-stage patients.
Article
Computer Science, Artificial Intelligence
S. Qasim Abbas, Lianhua Chi, Yi-Ping Phoebe Chen
Summary: The growing prevalence of neurological disorders demands robust computer-aided diagnosis. A benchmark neuroimaging diagnostics is absent for Autism Spectrum Disorder. Existing CADs using multisite data face variabilities and heterogeneities. To resolve this problem, a Deep Multimodal Neuroimaging Framework (DeepMNF) is proposed that integrates cross-modality spatiotemporal information. It achieves superior validation performance and demonstrates the effectiveness of multimodal framework development.
ARTIFICIAL INTELLIGENCE IN MEDICINE
(2023)
Review
Biochemical Research Methods
Wei Lan, Yi Dong, Hongyu Zhang, Chunling Li, Qingfeng Chen, Jin Liu, Jianxin Wang, Yi-Ping Phoebe Chen
Summary: Accumulating evidence shows the importance of circular RNA (circRNA) in human diseases. Computational methods have been proposed to identify circRNA-disease associations, but there is a lack of comprehensive comparisons and summaries of these methods. This paper categorizes existing methods into three groups and introduces baseline methods for each category. It compares 14 representative methods using 5 different datasets and evaluates their effectiveness in identifying circRNA-disease associations in common cancers. The study also discusses the observations about method robustness and future directions and challenges.
BRIEFINGS IN BIOINFORMATICS
(2023)
Article
Computer Science, Theory & Methods
Abukari Mohammed Yakubu, Yi Ping Phoebe Chen
Summary: Genomic data repositories are expanding rapidly, driven by the decrease in DNA sequencing costs. However, the current business model of direct-to-consumer genomic companies puts customers' privacy at risk and limits their control and access to their own genomic data. This paper proposes a system based on blockchain technology and homomorphic computation to address these issues, allowing genomic data owners to control their data and sell access to it, while enabling secure queries for genomic data users. The proposed scheme also includes optimization techniques to improve query response time and a penalty mechanism to discourage malicious behaviors. Experimental results demonstrate the feasibility and efficiency of the proposed system.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2022)
Article
Computer Science, Artificial Intelligence
Omar A. M. Salem, Feng Liu, Yi-Ping Phoebe Chen, Ahmed Hamed, Xi Chen
Summary: This paper investigates the challenge of data quality in classification problems and proposes an instance selection method based on uncertainty region (ISUR) and a feature selection method called fuzzy joint mutual information feature selection based on uncertainty region (FJMIUR). Experimental results demonstrate the superior performance of FJMIUR across multiple classification measures.
KNOWLEDGE-BASED SYSTEMS
(2022)
Article
Computer Science, Artificial Intelligence
S. Qasim Abbas, Lianhua Chi, Yi-Ping Phoebe Chen
Summary: Structural magnetic resonance imaging (sMRI) is a prevalent and potent imaging modality for the computer-aided diagnosis (CAD) of neurological diseases like dementia. Recent advancements in deep learning, particularly convolutional neural networks (CNNs), have shown promise in diagnosing Alzheimer's disease (AD) by learning the atrophy patterns in sMRIs. However, the current CNN-based approaches still need to improve their diagnostic performance. To address this issue, the proposed three-dimensional Jacobian domain convolutional neural network (JD-CNN) offers excellent classification performance without the need for landmark detection. The JD-CNN model is trained based on features transformed from the spatial domain to the Jacobian domain, and it surpasses previously reported state-of-the-art techniques in terms of classification performance.
PATTERN RECOGNITION
(2023)
Article
Computer Science, Information Systems
Timothy McIntosh, A. S. M. Kayes, Yi-Ping Phoebe Chen, Alex Ng, Paul Watters
Summary: The advancement of modern OSs and personal computing devices with Internet connectivity have led to a proliferation of ransomware attacks. This study proposes an updated ransomware threat model and a staged event-driven access control approach to combat ransomware. A prototype on Windows OS demonstrates the effectiveness of the proposed design in intercepting various ransomware attack vectors.
COMPUTERS & SECURITY
(2023)
Article
Biology
Min Luo, Zhen He, Hui Cui, Yi-Ping Phoebe Chen, Phillip Ward
Summary: We propose a novel attention transfer method for accurately predicting the progression of Alzheimer's disease (AD) in patients with mild cognitive impairment (MCI). Our method trains a 3D convolutional neural network to automatically learn regions of interest (ROI) from images and transfer attention maps instead of model weights. Our method outperformed traditional transfer learning and methods using expert knowledge to define ROI, and the attention map revealed Alzheimer's pathology.
COMPUTERS IN BIOLOGY AND MEDICINE
(2023)
Article
Engineering, Electrical & Electronic
Peng Cheng, Youjia Chen, Ming Ding, Zhuo Chen, Sige Liu, Yi-Ping Phoebe Chen
Summary: The growing number of complex and heterogeneous IoT applications requires efficient online resource allocation strategies. This article presents a DRL-based framework for resource allocation, discussing DRL basics, recent applications, and developing two new algorithms. The first algorithm tackles optimization problems with mixed action spaces and non-linear QoS constraints, while the second extends single-agent DRL to multi-agent DRL with a novel semi-distributed architecture. Challenges and future visions of applying DRL to real-world IoT networks are also discussed.
IEEE COMMUNICATIONS MAGAZINE
(2023)
Article
Biology
Raid Halawani, Michael Buchert, Yi-Ping Phoebe Chen
Summary: Tumour heterogeneity is a critical aspect in understanding tumour growth, and single-cell and spatial transcriptomics sequencing have emerged as key technologies for unraveling this heterogeneity. However, analyzing these data types poses challenges due to noise, sparsity, and dropouts. Deep learning frameworks show promise in overcoming these challenges and advancing precision oncology applications.
COMPUTERS IN BIOLOGY AND MEDICINE
(2023)
Proceedings Paper
Computer Science, Artificial Intelligence
Geetanjli Sharma, M. A. P. Chamikara, Mohan Baruwal Chhetri, Yi-Ping Phoebe Chen
Summary: Federated Learning (FL) is a machine learning technique that allows multiple parties to train a model using their own private datasets. However, FL is vulnerable to adversarial attacks due to its decentralized nature. To address the lack of comprehensive comparison and evaluation of FL attack studies, we propose a causal model that captures the impact of different factors on the success of an attack and validate it through experimental evaluation.
PROCEEDINGS OF THE 2023 ACM ASIA CONFERENCE ON COMPUTER AND COMMUNICATIONS SECURITY, ASIA CCS 2023
(2023)
Article
Computer Science, Artificial Intelligence
Ming-Hao Tung, Yi-Ping Phoebe Chen, Chen-Yu Liu, Chung-Shou Liao
Summary: A more accurate clustering algorithm called SDP is proposed, which is shown to be more accurate than the DP algorithm in handling clusters with relatively high densities, while maintaining similar running time. Moreover, SDP outperforms DP in the dynamic model where data point insertion and deletion are allowed.
IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING
(2023)
Article
Computer Science, Artificial Intelligence
Yu Zheng, Huan Yee Koh, Ming Jin, Lianhua Chi, Khoa T. Phan, Shirui Pan, Yi-Ping Phoebe Chen, Wei Xiang
Summary: Multivariate time-series anomaly detection is crucial in various applications, but existing methods have limitations in capturing nonlinear relations and explicit pairwise correlations. To address these issues, we propose a novel method called CST-GL, which explicitly captures pairwise correlations and utilizes a graph neural network to encode spatial information and capture long-range dependence over time.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2023)
Proceedings Paper
Computer Science, Artificial Intelligence
Jianggang Zhu, Zheng Wang, Jingjing Chen, Yi-Ping Phoebe Chen, Yu-Gang Jiang
Summary: This paper focuses on representation learning for imbalanced data and proposes a balanced contrastive learning (BCL) method that enhances the representation and classification of tail classes through two improvements: class-averaging and class-complement. Equipped with the proposed two-branch framework, competitive performance can be achieved on long-tailed benchmark datasets.
2022 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR 2022)
(2022)
Proceedings Paper
Computer Science, Artificial Intelligence
Omar A. M. Salem, Haowen Liu, Feng Liu, Yi-Ping Phoebe Chen, Xi Chen
Summary: Feature selection (FS) is important for improving classification performance. Fuzzy information measures are powerful in extracting feature relations without information loss, but they consume high resources. This paper proposes a novel method using descriptive statistics data (DS) to generate FS, which reduces cost while maintaining performance.
KNOWLEDGE SCIENCE, ENGINEERING AND MANAGEMENT, KSEM 2022, PT III
(2022)
Article
Computer Science, Information Systems
Bohong Yang, Wu Ran, Lin Wang, Hong Lu, Yi-Ping Phoebe Chen
Summary: In this paper, a novel Multi-classes and motion properties for Concurrent Visual SLAM (MCV-SLAM) algorithm is proposed, which defines classes into five categories and concurrently fuses prior knowledge and observation of moving objects with semantic segmentation to ensure visual SLAM works properly for dynamic environments in real time.
IEEE TRANSACTIONS ON MULTIMEDIA
(2022)