AIMC Topic: RNA, Long Noncoding

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Deep Learning Approaches for lncRNA-Mediated Mechanisms: A Comprehensive Review of Recent Developments.

International journal of molecular sciences
This review paper provides an extensive analysis of the rapidly evolving convergence of deep learning and long non-coding RNAs (lncRNAs). Considering the recent advancements in deep learning and the increasing recognition of lncRNAs as crucial compon...

An Optimized Ensemble Deep Learning Model for Predicting Plant miRNA-IncRNA Based on Artificial Gorilla Troops Algorithm.

Sensors (Basel, Switzerland)
MicroRNAs (miRNA) are small, non-coding regulatory molecules whose effective alteration might result in abnormal gene manifestation in the downstream pathway of their target. miRNA gene variants can impact miRNA transcription, maturation, or target s...

Finding lncRNA-Protein Interactions Based on Deep Learning With Dual-Net Neural Architecture.

IEEE/ACM transactions on computational biology and bioinformatics
The identification of lncRNA-protein interactions (LPIs) is important to understand the biological functions and molecular mechanisms of lncRNAs. However, most computational models are evaluated on a unique dataset, thereby resulting in prediction bi...

DeepPlnc: Bi-modal deep learning for highly accurate plant lncRNA discovery.

Genomics
We present here a bi-modal CNN based deep-learning system, DeepPlnc, to identify plant lncRNAs with high accuracy while using sequence and structural properties. Unlike most of the existing software, it works accurately even in conditions with ambigu...

MD-MLI: Prediction of miRNA-lncRNA Interaction by Using Multiple Features and Hierarchical Deep Learning.

IEEE/ACM transactions on computational biology and bioinformatics
Long non-coding RNA(lncRNA) can interact with microRNA(miRNA) and play an important role in inhibiting or activating the expression of target genes and the occurrence and development of tumors. Accumulating studies focus on the prediction of miRNA-ln...

LDICDL: LncRNA-Disease Association Identification Based on Collaborative Deep Learning.

IEEE/ACM transactions on computational biology and bioinformatics
It has been proved that long noncoding RNA (lncRNA) plays critical roles in many human diseases. Therefore, inferring associations between lncRNAs and diseases can contribute to disease diagnosis, prognosis and treatment. To overcome the limitation o...

Machine learning-based integration develops an immune-derived lncRNA signature for improving outcomes in colorectal cancer.

Nature communications
Long noncoding RNAs (lncRNAs) are recently implicated in modifying immunology in colorectal cancer (CRC). Nevertheless, the clinical significance of immune-related lncRNAs remains largely unexplored. In this study, we develope a machine learning-base...

DMFLDA: A Deep Learning Framework for Predicting lncRNA-Disease Associations.

IEEE/ACM transactions on computational biology and bioinformatics
A growing amount of evidence suggests that long non-coding RNAs (lncRNAs) play important roles in the regulation of biological processes in many human diseases. However, the number of experimentally verified lncRNA-disease associations is very limite...

Demystifying the long noncoding RNA landscape of small EVs derived from human mesenchymal stromal cells.

Journal of advanced research
INTRODUCTION: The regenerative capacity of mesenchymal stromal cells or medicinal signaling cells (MSCs) is largely mediated by their secreted small extracellular vesicles (sEVs), and the therapeutic efficacy of sEVs can be enhanced by licensing appr...

Multi-Run Concrete Autoencoder to Identify Prognostic lncRNAs for 12 Cancers.

International journal of molecular sciences
BACKGROUND: Long non-coding RNA plays a vital role in changing the expression profiles of various target genes that lead to cancer development. Thus, identifying prognostic lncRNAs related to different cancers might help in developing cancer therapy.