Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

RNA-sequencing and swarm intelligence-enhanced classification algorithm development for blood-based disease diagnostics using spliced blood platelet RNA

ABSTRACT: RNA-sequencing and swarm intelligence-enhanced classification algorithm development for blood-based disease diagnostics using spliced blood platelet RNA

PROVIDER: PRJNA421730 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	SRR6363430.fastq.gz	Fastqsanger.gz
	SRR6363440.fastq.gz	Fastqsanger.gz
	SRR6363450.fastq.gz	Fastqsanger.gz
	SRR6363460.fastq.gz	Fastqsanger.gz
	SRR6363470.fastq.gz	Fastqsanger.gz

Items per page:

1 - 5 of 80

Similar Datasets

RNA-sequencing and swarm intelligence-enhanced classification algorithm development for blood-based disease diagnostics using spliced blood platelet RNA

Project description:We report RNA-sequencing data of 80 tumor-educated blood platelet (TEP) samples isolated from 39 patients with lower-grade glioma (LGG) and 41 healthy donors (HD). This dataset can be employed as input for the thromboSeq source code (available via GitHub: https://github.com/MyronBest/) to reproduce the thromboSeq drylab pipeline.

2019-03-20 | GSE107868 | GEO

5-aza-2-deoxycytidine treatment of Swarm rat chondrosarcoma cells

Project description:The puropose of this experiment was to identify gene expression changes that result from 5-aza-2-deoxycytidine induced DNA demethylation of Swarm rat chondrosarcoma cells. The gene expression profiles of untreated Swarm rat chondrosarcoma cells were compared to the gene expression profiles of Swarm rat chondrosarcoma cells that were treated for 5 passages with a low dose of 5-aza-2-deoxycytidine (0.1uM). Five chip study. For these experiments, microarray was carried out on untreated (control) Swarm rat chondrosarcoma cells (3 biological replicates), and microarray was also carried out on Swarm rat chondrosarcoma cells treated with 5-aza-2-deoxycytidine (2 biological replicates).

2010-08-06 | E-GEOD-17598 | biostudies-arrayexpress

5-aza-2-deoxycytidine treatment of Swarm rat chondrosarcoma cells

2010-08-06 | GSE17598 | GEO

AGA algorithm

Project description:Aminoglycosides resistance mechanisms inference algorithm

| PRJEB29576 | ENA

Swarm intelligence-enhanced detection of non-small cell lung cancer using tumor-educated platelets

Project description:We report RNA-sequencing data of 779 blood platelet samples, including 402 tumor-educated platelet (TEP) samples collected from patients with non-small cell lung cancer (NSCLC). In addition, we report RNA-sequencing data of blood platelets isolated from 377 individuals without reported cancer, but not excluding individuals with inflammatory conditions. This dataset highlights the ability of TEP RNA-based 'liquid biopsy' diagnostics in patients with NSCLC.

2017-08-15 | GSE89843 | GEO

Particle Swarm Optimization and Salp Swarm Algorithm for the Segmentation of Diabetic Retinal Blood Vessel Images.

Project description:In recent years, the incidence of diabetes has been increasing year by year. Since most of the fundus lesions are located near blood vessels, the image information is complex, and the end vessels are difficult to identify. So, a new segmentation method of diabetic retinal vessel images based on particle swarm optimization and salp swarm algorithm is proposed. This paper uses a Gaussian filter to enhance the main blood vessels, and a top-bot hat transform is used to strengthen the end vessels. The preprocessing process is completed by combining and reconstructing the two images through a normalization operation. The improved particle swarm optimization and salp swarm algorithms perform multi-threshold segmentation on the preprocessed vessel images. The best fit value, Structural Similarity Index Measure, Peak Signal to Noise Rati, feature similarity index measure, sensitivity, accuracy, regional consistency, Dice coefficient, Jaccard similarity, and Shannon entropy are selected for comprehensive evaluation and analysis. The results showed that this paper's improved particle swarm-salp swarm algorithm for segmenting diabetic retinal blood vessel images is more efficient, and the threshold is better. The vascular segmentation method in this paper is applied in medical image processing, which improves the accuracy of medical image processing and reduces the computational effort.

| S-EPMC9427232 | biostudies-literature

ddRADseq analysis of a hybrid swarm

Project description:Fine scale description of hybrid classes in a hybrid swarm

| PRJEB24320 | ENA

Swarm Learning to identify COVID-19, tuberculosis and leukemia patients based on blood transcriptomes

Project description:Identification of patients with life-threatening diseases including leukemias or infections such as tuberculosis or COVID-19 is an important goal of modern precision medicine. However, there is an increasing divide between what is technically possible and what is allowed because of privacy legislation. We have recently illustrated that classical machine learning can identify leukemia patients based on their blood transcriptomes. To facilitate integration of any omics data from any data owner world-wide without violating privacy laws, we here introduce Swarm Learning (SL), a decentralized machine learning approach uniting edge computing, artificial intelligence (AI), blockchain and privacy protection without the need for a central coordinator thereby going beyond federated learning. To illustrate its feasibility, using more than 12,000 transcriptomes from peripheral blood mononuclear cells and more than 2,000 peripheral blood transcriptomes we demonstrate that SL of omics data distributed across different individual sites leads to disease classifiers that outperform those developed at individual sites. Yet, SL completely protects local privacy regulations by design. We propose this approach to noticeably accelerate the introduction of precision medicine.

| EGAS00001004502 | EGA

Higher intelligence is genetically linked with longevity

Project description:Higher intelligence is genetically linked with longevity

| PRJNA819011 | ENA

Higher intelligence is genetically linked with longevity

Project description:We report the application of mRNA sequencing technology for identifying that the genetic linkage of higher intelligence with longevity in Drosophilla melanogaster. a transcriptome analysis was performed by sequencing the total mRNA. The differentially expressed gene analysis by a negative binomial test showed that a subset of genes displayed remarkably altered expression where 56, 152, and 26 genes were significantly upregulated (adjusted P value <0.01), and 30, 397, and 10 genes were downregulated (adjusted P value < 0.01) in INT compared to F0, NINT compared to F0, and INT compared to NINT each. The functions of the differentially expressed genes were analyzed at high levels by using Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment program. Compared to F0, the pathways of ribosome and autophagy were up-regulated in INT while the pathways related to metabolisms were down-regulated. Meanwhile, the pathways associated with genome stability and immune reaction was upregulated and the pathway of oxidative phosphorylation responsible for ATP generation was down regulated in NINT. The KEGG comparison of INT with NINT, which eliminates genes associated with the environmental factors during the selection process, visualized more precise pathways associated with higher intelligence and longevity. The pathways related to genome stability (Fanconi anemia pathway, Mismatch repair, DNA replication, Homologous recombination, and Nucleotide excision repair) and immune reaction (Toll and lmd signaling pathway) were up-regulated in NINT, and these pathways were down-regulated in INT.

2023-02-17 | GSE196981 | GEO

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data