Blood RNA-Seq profiling reveals a set of circular RNAs differentially expressed in frail individuals

to related objects

Location: Deutsche Nationalbibliothek Frankfurt am Main

Extent: Online-Ressource, 1 online resource.

Language: Englisch

Bibliographic citation: Blood RNA-Seq profiling reveals a set of circular RNAs differentially expressed in frail individuals ; volume:20 ; number:1 ; day:11 ; month:7 ; year:2023 ; pages:1-11 ; date:12.2023
Immunity & ageing ; 20, Heft 1 (11.7.2023), 1-11, 12.2023

Creator: Iparraguirre, Leire
Alberro, Ainhoa
Iñiguez, Saioa GS
Muñoz-Culla, Maider
Vergara, Itziar
Matheu, Ander
Otaegui, David

Contributor: SpringerLink (Online service)

DOI: 10.1186/s12979-023-00356-6

URN: urn:nbn:de:101:1-2023101308172063089650

Rights: Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.

Last update: 14.08.2025, 10:57 AM CEST

Data provider

This object is provided by:
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.

Show original at data provider

Associated

Iparraguirre, Leire
Alberro, Ainhoa
Iñiguez, Saioa GS
Muñoz-Culla, Maider
Vergara, Itziar
Matheu, Ander
Otaegui, David
SpringerLink (Online service)

Other Objects (12)

Robustness of single-cell RNA-seq for identifying differentially expressed genes

Statistical methods on detecting differentially expressed genes for RNA-seq data

Modeling and cleaning RNA-seq data significantly improve detection of differentially expressed genes

OVCH1 Antisense RNA 1 is differentially expressed between non-frail and frail old adults

A scaling-free minimum enclosing ball method to detect differentially expressed genes for RNA-seq data

Characterisation of genes differentially expressed in macrophages by virulent and attenuated Mycobacterium tuberculosis through RNA-Seq analysis

Study on differentially expressed genes related to defoliation traits in two alfalfa varieties based on RNA-Seq

BALLI: Bartlett-adjusted likelihood-based linear model approach for identifying differentially expressed genes with RNA-seq data

Comparative analysis of differentially expressed genes between the ovaries from pregnant and nonpregnant goats using RNA-Seq

Identification of differentially expressed genes based on antennae RNA-seq analyses in Culex quinquefasciatus and Culex pipiens molestus

DEGnext: classification of differentially expressed genes from RNA-seq data using a convolutional neural network with transfer learning

EPIG-Seq: extracting patterns and identifying co-expressed genes from RNA-Seq data

Robustness of single-cell RNA-seq for identifying differentially expressed genes

Statistical methods on detecting differentially expressed genes for RNA-seq data

Modeling and cleaning RNA-seq data significantly improve detection of differentially expressed genes

OVCH1 Antisense RNA 1 is differentially expressed between non-frail and frail old adults

A scaling-free minimum enclosing ball method to detect differentially expressed genes for RNA-seq data

Characterisation of genes differentially expressed in macrophages by virulent and attenuated Mycobacterium tuberculosis through RNA-Seq analysis

Study on differentially expressed genes related to defoliation traits in two alfalfa varieties based on RNA-Seq

BALLI: Bartlett-adjusted likelihood-based linear model approach for identifying differentially expressed genes with RNA-seq data

Comparative analysis of differentially expressed genes between the ovaries from pregnant and nonpregnant goats using RNA-Seq

Identification of differentially expressed genes based on antennae RNA-seq analyses in Culex quinquefasciatus and Culex pipiens molestus

DEGnext: classification of differentially expressed genes from RNA-seq data using a convolutional neural network with transfer learning

EPIG-Seq: extracting patterns and identifying co-expressed genes from RNA-Seq data

Robustness of single-cell RNA-seq for identifying differentially expressed genes

Statistical methods on detecting differentially expressed genes for RNA-seq data

Modeling and cleaning RNA-seq data significantly improve detection of differentially expressed genes

OVCH1 Antisense RNA 1 is differentially expressed between non-frail and frail old adults

A scaling-free minimum enclosing ball method to detect differentially expressed genes for RNA-seq data

Characterisation of genes differentially expressed in macrophages by virulent and attenuated Mycobacterium tuberculosis through RNA-Seq analysis

Study on differentially expressed genes related to defoliation traits in two alfalfa varieties based on RNA-Seq

BALLI: Bartlett-adjusted likelihood-based linear model approach for identifying differentially expressed genes with RNA-seq data

Comparative analysis of differentially expressed genes between the ovaries from pregnant and nonpregnant goats using RNA-Seq

Identification of differentially expressed genes based on antennae RNA-seq analyses in Culex quinquefasciatus and Culex pipiens molestus

DEGnext: classification of differentially expressed genes from RNA-seq data using a convolutional neural network with transfer learning

EPIG-Seq: extracting patterns and identifying co-expressed genes from RNA-Seq data

Cultural heritage institutions wishing to register will find more information here.

Fields marked * need to be filled in.

Username*

Please enter your username

Email*

Please enter your email address

Please do not fill this field

First name

Last name

Password*

Please enter your password

Confirm password*

Please enter the same password

I have read the terms of use and the privacy policy for the collection of personal data and accept them. *

This field is required.

I would like to subscribe to the newsletter of the Deutsche Digitale Bibliothek. See newsletter subscription info.

Account created

Your "My DDB" account has been successfully created. Before you can log in to your account, you must click the confirmation link in the message we just sent to the email address you provided.

Blood RNA-Seq profiling reveals a set of circular RNAs differentially expressed in frail individuals

Object Details

References and Relationships

Contributors, Places and Time

Further information

Data provider

Associated

Other Objects (12)

Robustness of single-cell RNA-seq for identifying differentially expressed genes

Statistical methods on detecting differentially expressed genes for RNA-seq data

Modeling and cleaning RNA-seq data significantly improve detection of differentially expressed genes

OVCH1 Antisense RNA 1 is differentially expressed between non-frail and frail old adults

A scaling-free minimum enclosing ball method to detect differentially expressed genes for RNA-seq data

Characterisation of genes differentially expressed in macrophages by virulent and attenuated Mycobacterium tuberculosis through RNA-Seq analysis

Study on differentially expressed genes related to defoliation traits in two alfalfa varieties based on RNA-Seq

BALLI: Bartlett-adjusted likelihood-based linear model approach for identifying differentially expressed genes with RNA-seq data

Comparative analysis of differentially expressed genes between the ovaries from pregnant and nonpregnant goats using RNA-Seq

Identification of differentially expressed genes based on antennae RNA-seq analyses in Culex quinquefasciatus and Culex pipiens molestus

DEGnext: classification of differentially expressed genes from RNA-seq data using a convolutional neural network with transfer learning

EPIG-Seq: extracting patterns and identifying co-expressed genes from RNA-Seq data

Robustness of single-cell RNA-seq for identifying differentially expressed genes

Statistical methods on detecting differentially expressed genes for RNA-seq data

Modeling and cleaning RNA-seq data significantly improve detection of differentially expressed genes

OVCH1 Antisense RNA 1 is differentially expressed between non-frail and frail old adults

A scaling-free minimum enclosing ball method to detect differentially expressed genes for RNA-seq data

Characterisation of genes differentially expressed in macrophages by virulent and attenuated Mycobacterium tuberculosis through RNA-Seq analysis

Study on differentially expressed genes related to defoliation traits in two alfalfa varieties based on RNA-Seq

BALLI: Bartlett-adjusted likelihood-based linear model approach for identifying differentially expressed genes with RNA-seq data

Comparative analysis of differentially expressed genes between the ovaries from pregnant and nonpregnant goats using RNA-Seq

Identification of differentially expressed genes based on antennae RNA-seq analyses in Culex quinquefasciatus and Culex pipiens molestus

DEGnext: classification of differentially expressed genes from RNA-seq data using a convolutional neural network with transfer learning

EPIG-Seq: extracting patterns and identifying co-expressed genes from RNA-Seq data

Robustness of single-cell RNA-seq for identifying differentially expressed genes

Statistical methods on detecting differentially expressed genes for RNA-seq data

Modeling and cleaning RNA-seq data significantly improve detection of differentially expressed genes

OVCH1 Antisense RNA 1 is differentially expressed between non-frail and frail old adults

A scaling-free minimum enclosing ball method to detect differentially expressed genes for RNA-seq data

Characterisation of genes differentially expressed in macrophages by virulent and attenuated Mycobacterium tuberculosis through RNA-Seq analysis

Study on differentially expressed genes related to defoliation traits in two alfalfa varieties based on RNA-Seq

BALLI: Bartlett-adjusted likelihood-based linear model approach for identifying differentially expressed genes with RNA-seq data

Comparative analysis of differentially expressed genes between the ovaries from pregnant and nonpregnant goats using RNA-Seq

Identification of differentially expressed genes based on antennae RNA-seq analyses in Culex quinquefasciatus and Culex pipiens molestus

DEGnext: classification of differentially expressed genes from RNA-seq data using a convolutional neural network with transfer learning

EPIG-Seq: extracting patterns and identifying co-expressed genes from RNA-Seq data

Related objects

Reset password