AIMC Topic: RNA, Small Interfering
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Identification of lead anti-human cytomegalovirus compounds targeting MAP4K4 via machine learning analysis of kinase inhibitor screening data.
PloS one
Jul 26, 2018
Chemogenomic approaches involving highly annotated compound sets and cell based high throughput screening are emerging as a means to identify novel drug targets. We have previously screened a collection of highly characterized kinase inhibitors (Khan...
Effective computational detection of piRNAs using n-gram models and support vector machine.
BMC bioinformatics
Dec 28, 2017
BACKGROUND: Piwi-interacting RNAs (piRNAs) are a new class of small non-coding RNAs that are known to be associated with RNA silencing. The piRNAs play an important role in protecting the genome from invasive transposons in the germline. Recent studi...
Digging deep into Golgi phenotypic diversity with unsupervised machine learning.
Molecular biology of the cell
Oct 11, 2017
The synthesis of glycans and the sorting of proteins are critical functions of the Golgi apparatus and depend on its highly complex and compartmentalized architecture. High-content image analysis coupled to RNA interference screening offers opportuni...
Using machine learning algorithms to identify genes essential for cell survival.
BMC bioinformatics
Oct 3, 2017
BACKGROUND: With the explosion of data comes a proportional opportunity to identify novel knowledge with the potential for application in targeted therapies. In spite of this huge amounts of data, the solutions to treating complex disease is elusive....
GuideScan software for improved single and paired CRISPR guide RNA design.
Nature biotechnology
Mar 6, 2017
We present GuideScan software for the design of CRISPR guide RNA libraries that can be used to edit coding and noncoding genomic regions. GuideScan produces high-density sets of guide RNAs (gRNAs) for single- and paired-gRNA genome-wide screens. We a...
Prediction of potent shRNAs with a sequential classification algorithm.
Nature biotechnology
Mar 6, 2017
We present SplashRNA, a sequential classifier to predict potent microRNA-based short hairpin RNAs (shRNAs). Trained on published and novel data sets, SplashRNA outperforms previous algorithms and reliably predicts the most efficient shRNAs for a give...
V-ELMpiRNAPred: Identification of human piRNAs by the voting-based extreme learning machine (V-ELM) with a new hybrid feature.
Journal of bioinformatics and computational biology
Jan 9, 2017
Piwi-interacting RNAs (piRNAs) were recently discovered as endogenous small noncoding RNAs. Some recent research suggests that piRNAs may play an important role in cancer. So the precise identification of human piRNAs is a significant work. In this p...
Computational identification of piRNA targets on mouse mRNAs.
Bioinformatics (Oxford, England)
Dec 16, 2015
MOTIVATION: PIWI-interacting RNAs (piRNAs) are a class of small non-coding RNAs that are highly abundant in the germline. One important role of piRNAs is to defend genome integrity by guiding PIWI proteins to silence transposable elements (TEs), whic...
A robust machine learning model based on ribosomal-subunit-derived piRNAs for diagnostic potential of nonsmall cell lung cancer across multicentre, large-scale of sequencing data.
Clinical and translational medicine
Aug 1, 2025
Nonsmall cell lung cancer (NSCLC) is a lethal cancer and lacks robust biomarkers for noninvasive clinical diagnosis. Detecting NSCLC at the early stage can decrease the mortality rate and minimise harm caused by various treatments. We curated 2050 sa...
Nanotechnology-Enhanced siRNA Delivery: Revolutionizing Cancer Therapy.
ACS applied bio materials
Jun 16, 2025
RNA interference (RNAi) has emerged as a transformative approach for cancer therapy, enabling precise gene silencing through small interfering RNA (siRNA). However, the clinical application of siRNA-based treatments faces challenges such as rapid deg...
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