LIVIVO - Search results -

Search results

Result 1 - 10 of total 3734

Search options

Article ; Online: Deep learning for detecting and elucidating human T-cell leukemia virus type 1 integration in the human genome.

Xu, Haodong / Jia, Johnathan / Jeong, Hyun-Hwan / Zhao, Zhongming

Patterns (New York, N.Y.)

2023 Volume 4, Issue 2, Page(s) 100674

Abstract: Human T-cell leukemia virus type 1 (HTLV-1), a retrovirus, is the causative agent for adult T cell leukemia/lymphoma and many other human diseases. Accurate and high throughput detection of HTLV-1 virus integration sites (VISs) across the host genomes ... ...

Abstract	Human T-cell leukemia virus type 1 (HTLV-1), a retrovirus, is the causative agent for adult T cell leukemia/lymphoma and many other human diseases. Accurate and high throughput detection of HTLV-1 virus integration sites (VISs) across the host genomes plays a crucial role in the prevention and treatment of HTLV-1-associated diseases. Here, we developed DeepHTLV, the first deep learning framework for VIS prediction
Language	English
Publishing date	2023-02-10
Publishing country	United States
Document type	Journal Article
ISSN	2666-3899
ISSN (online)	2666-3899
DOI	10.1016/j.patter.2022.100674
Database	MEDical Literature Analysis and Retrieval System OnLINE

Order via subito

This service is chargeable due to the Delivery terms set by subito. Orders including an article and supplementary material will be classified as separate orders. In these cases, fees will be demanded for each order.

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Article ; Online: Are HHV-6A and HHV-7 Really More Abundant in Alzheimer's Disease?

Jeong, Hyun-Hwan / Liu, Zhandong

Neuron

2019 Volume 104, Issue 6, Page(s) 1034–1035

MeSH term(s)	Alzheimer Disease ; Herpesvirus 6, Human ; Herpesvirus 7, Human ; Humans ; Roseolovirus Infections
Language	English
Publishing date	2019-12-19
Publishing country	United States
Document type	Letter ; Comment
ZDB-ID	808167-0
ISSN	1097-4199 ; 0896-6273
ISSN (online)	1097-4199
ISSN	0896-6273
DOI	10.1016/j.neuron.2019.11.009
Database	MEDical Literature Analysis and Retrieval System OnLINE

In stock of ZB MED Cologne/Königswinter

Zs.A 2496: Show issues			Location: Je nach Verfügbarkeit (siehe Angabe bei Bestand) bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular Jg. 1995 - 2021: Lesesall (2.OG) ab Jg. 2022: Lesesaal (EG)
Zs.MG 92: Show issues

Order via subito

Details ▾
- See ZB MED holdings
- Order with fees

Article ; Online: Obstructive Sleep Apnea and Dementia-Common Gene Associations through Network-Based Identification of Common Driver Genes.

Jeong, Hyun-Hwan / Chandrakantan, Arvind / Adler, Adam C

Genes

2021 Volume 12, Issue 4

Abstract: Background: Obstructive Sleep Apnea (OSA) occurs in 7% of the adult population. The relationship between neurodegenerative diseases such as dementia and sleep disorders have long attracted clinical attention; however, no comprehensive data exists ... ...

Abstract	Background: Obstructive Sleep Apnea (OSA) occurs in 7% of the adult population. The relationship between neurodegenerative diseases such as dementia and sleep disorders have long attracted clinical attention; however, no comprehensive data exists elucidating common gene expression between the two diseases. The objective of this study was to (1) demonstrate the practicability and feasibility of utilizing a systems biology approach called network-based identification of common driver genes (NICD) to identify common genomic features between two associated diseases and (2) utilize this approach to identify genes associated with both OSA and dementia. Methods: This study utilized 2 public databases (PCNet, DisGeNET) and a permutation assay in order to identify common genes between two co-morbid but mutually exclusive diseases. These genes were then linked to their mechanistic pathways through Enrichr, producing a list of genes that were common between the two different diseases. Results: 42 common genes were identified between OSA and dementia which were primarily linked to the G-coupled protein receptor (GPCR) and olfactory pathways. No single nucleotide polymorphisms (SNPs) were identified. Conclusions: This study demonstrates the viability of using publicly available databases and permutation assays along with canonical pathway linkage to identify common gene drivers as potential mechanistic targets for comorbid diseases.
MeSH term(s)	Biomarkers/analysis ; Computational Biology/methods ; Databases, Genetic ; Dementia/complications ; Dementia/genetics ; Dementia/pathology ; Gene Expression Regulation ; Humans ; Polymorphism, Single Nucleotide ; Sleep Apnea, Obstructive/complications ; Sleep Apnea, Obstructive/genetics ; Sleep Apnea, Obstructive/pathology ; Systems Biology
Chemical Substances	Biomarkers
Language	English
Publishing date	2021-04-09
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2527218-4
ISSN	2073-4425 ; 2073-4425
ISSN (online)	2073-4425
ISSN	2073-4425
DOI	10.3390/genes12040542
Database	MEDical Literature Analysis and Retrieval System OnLINE

Order via subito

Article: Obstructive Sleep Apnea and Dementia-Common Gene Associations through Network-Based Identification of Common Driver Genes

Jeong, Hyun-Hwan / Chandrakantan, Arvind / Adler, Adam C

Genes. 2021 Apr. 09, v. 12, no. 4

2021

Abstract	Background: Obstructive Sleep Apnea (OSA) occurs in 7% of the adult population. The relationship between neurodegenerative diseases such as dementia and sleep disorders have long attracted clinical attention; however, no comprehensive data exists elucidating common gene expression between the two diseases. The objective of this study was to (1) demonstrate the practicability and feasibility of utilizing a systems biology approach called network-based identification of common driver genes (NICD) to identify common genomic features between two associated diseases and (2) utilize this approach to identify genes associated with both OSA and dementia. Methods: This study utilized 2 public databases (PCNet, DisGeNET) and a permutation assay in order to identify common genes between two co-morbid but mutually exclusive diseases. These genes were then linked to their mechanistic pathways through Enrichr, producing a list of genes that were common between the two different diseases. Results: 42 common genes were identified between OSA and dementia which were primarily linked to the G-coupled protein receptor (GPCR) and olfactory pathways. No single nucleotide polymorphisms (SNPs) were identified. Conclusions: This study demonstrates the viability of using publicly available databases and permutation assays along with canonical pathway linkage to identify common gene drivers as potential mechanistic targets for comorbid diseases.
Keywords	adults ; dementia ; gene expression ; genes ; genomics ; sleep ; sleep apnea
Language	English
Dates of publication	2021-0409
Publishing place	Multidisciplinary Digital Publishing Institute
Document type	Article
Note	NAL-AP-2-clean
ZDB-ID	2527218-4
ISSN	2073-4425
ISSN	2073-4425
DOI	10.3390/genes12040542
Database	NAL-Catalogue (AGRICOLA)

Order via subito

Article ; Online: PANoptosis is a prominent feature of desmoplakin cardiomyopathy.

Olcum, Melis / Rouhi, Leila / Fan, Siyang / Gonzales, Maya M / Jeong, Hyun-Hwan / Zhao, Zhongming / Gurha, Priyatansh / Marian, Ali J

The journal of cardiovascular aging

2023 Volume 3, Issue 1

Abstract: Introduction: Arrhythmogenic cardiomyopathy (ACM) is hereditary cardiomyopathy caused by pathogenic variants (mutations) in genes encoding the intercalated disc (ID), particularly desmosome proteins. ACM caused by mutations in the : Aim: The aim of ... ...

Abstract	Introduction: Arrhythmogenic cardiomyopathy (ACM) is hereditary cardiomyopathy caused by pathogenic variants (mutations) in genes encoding the intercalated disc (ID), particularly desmosome proteins. ACM caused by mutations in the Aim: The aim of this article was to gain insight into the pathogenesis of DSP cardiomyopathy. Methods and results: The Conclusion: The findings identify PANoptosis as a prominent phenotypic feature of DSP cardiomyopathy and set the stage for delineating the specific molecular mechanisms involved in its pathogenesis. The model also provides the opportunity to test the effects of pharmacological and genetic interventions on myocardial fibrosis and cell death.
Language	English
Publishing date	2023-01-01
Publishing country	United States
Document type	Journal Article
ISSN	2768-5993
ISSN (online)	2768-5993
DOI	10.20517/jca.2022.34
Database	MEDical Literature Analysis and Retrieval System OnLINE

Order via subito

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Article ; Online: Literature-based predictions of Mendelian disease therapies.

Deisseroth, Cole A / Lee, Won-Seok / Kim, Jiyoen / Jeong, Hyun-Hwan / Dhindsa, Ryan S / Wang, Julia / Zoghbi, Huda Y / Liu, Zhandong

American journal of human genetics

2023 Volume 110, Issue 10, Page(s) 1661–1672

Abstract: In the effort to treat Mendelian disorders, correcting the underlying molecular imbalance may be more effective than symptomatic treatment. Identifying treatments that might accomplish this goal requires extensive and up-to-date knowledge of molecular ... ...

Abstract	In the effort to treat Mendelian disorders, correcting the underlying molecular imbalance may be more effective than symptomatic treatment. Identifying treatments that might accomplish this goal requires extensive and up-to-date knowledge of molecular pathways-including drug-gene and gene-gene relationships. To address this challenge, we present "parsing modifiers via article annotations" (PARMESAN), a computational tool that searches PubMed and PubMed Central for information to assemble these relationships into a central knowledge base. PARMESAN then predicts putatively novel drug-gene relationships, assigning an evidence-based score to each prediction. We compare PARMESAN's drug-gene predictions to all of the drug-gene relationships displayed by the Drug-Gene Interaction Database (DGIdb) and show that higher-scoring relationship predictions are more likely to match the directionality (up- versus down-regulation) indicated by this database. PARMESAN had more than 200,000 drug predictions scoring above 8 (as one example cutoff), for more than 3,700 genes. Among these predicted relationships, 210 were registered in DGIdb and 201 (96%) had matching directionality. This publicly available tool provides an automated way to prioritize drug screens to target the most-promising drugs to test, thereby saving time and resources in the development of therapeutics for genetic disorders.
MeSH term(s)	Humans ; PubMed ; Databases, Factual
Language	English
Publishing date	2023-09-22
Publishing country	United States
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
ZDB-ID	219384-x
ISSN	1537-6605 ; 0002-9297
ISSN (online)	1537-6605
ISSN	0002-9297
DOI	10.1016/j.ajhg.2023.08.018
Database	MEDical Literature Analysis and Retrieval System OnLINE

Full text online

Accessible to users with ZB MED library card

In stock of ZB MED Cologne/Königswinter

Zs.A 107: Show issues

Location:
Je nach Verfügbarkeit (siehe Angabe bei Bestand)
bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
Jg. 1995 - 2021: Lesesall (1.OG)
ab Jg. 2022: Lesesaal (EG)

Order via subito

Details ▾

Article ; Online: ClearF

Sehee Wang / Hyun-Hwan Jeong / Kyung-Ah Sohn

BMC Medical Genomics, Vol 12, Iss S5, Pp 1-

a supervised feature scoring method to find biomarkers using class-wise embedding and reconstruction

2019 Volume 12

Abstract: Abstract Background Feature selection or scoring methods for the detection of biomarkers are essential in bioinformatics. Various feature selection methods have been developed for the detection of biomarkers, and several studies have employed information- ...

Abstract	Abstract Background Feature selection or scoring methods for the detection of biomarkers are essential in bioinformatics. Various feature selection methods have been developed for the detection of biomarkers, and several studies have employed information-theoretic approaches. However, most of these methods generally require a long processing time. In addition, information-theoretic methods discretize continuous features, which is a drawback that can lead to the loss of information. Results In this paper, a novel supervised feature scoring method named ClearF is proposed. The proposed method is suitable for continuous-valued data, which is similar to the principle of feature selection using mutual information, with the added advantage of a reduced computation time. The proposed score calculation is motivated by the association between the reconstruction error and the information-theoretic measurement. Our method is based on class-wise low-dimensional embedding and the resulting reconstruction error. Given multi-class datasets such as a case-control study dataset, low-dimensional embedding is first applied to each class to obtain a compressed representation of the class, and also for the entire dataset. Reconstruction is then performed to calculate the error of each feature and the final score for each feature is defined in terms of the reconstruction errors. The correlation between the information theoretic measurement and the proposed method is demonstrated using a simulation. For performance validation, we compared the classification performance of the proposed method with those of various algorithms on benchmark datasets. Conclusions The proposed method showed higher accuracy and lower execution time than the other established methods. Moreover, an experiment was conducted on the TCGA breast cancer dataset, and it was confirmed that the genes with the highest scores were highly associated with subtypes of breast cancer.
Keywords	Feature selection ; Feature scoring ; Mutual information (MI) ; Breast cancer ; Dimension reduction ; Low-dimensional embedding ; Internal medicine ; RC31-1245 ; Genetics ; QH426-470
Subject code	004
Language	English
Publishing date	2019-07-01T00:00:00Z
Publisher	BMC
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

Full text online

Full text

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Article ; Online: Genetic inactivation of β-catenin is salubrious, whereas its activation is deleterious in desmoplakin cardiomyopathy.

Olcum, Melis / Fan, Siyang / Rouhi, Leila / Cheedipudi, Sirisha / Cathcart, Benjamin / Jeong, Hyun-Hwan / Zhao, Zhongming / Gurha, Priyatansh / Marian, Ali J

Cardiovascular research

2023 Volume 119, Issue 17, Page(s) 2712–2728

Abstract: Aims: Mutations in the DSP gene encoding desmoplakin, a constituent of the desmosomes at the intercalated discs (IDs), cause a phenotype that spans arrhythmogenic cardiomyopathy (ACM) and dilated cardiomyopathy. It is typically characterized by ... ...

Abstract	Aims: Mutations in the DSP gene encoding desmoplakin, a constituent of the desmosomes at the intercalated discs (IDs), cause a phenotype that spans arrhythmogenic cardiomyopathy (ACM) and dilated cardiomyopathy. It is typically characterized by biventricular enlargement and dysfunction, myocardial fibrosis, cell death, and arrhythmias. The canonical wingless-related integration (cWNT)/β-catenin pathway is implicated in the pathogenesis of ACM. The β-catenin is an indispensable co-transcriptional regulator of the cWNT pathway and a member of the IDs. We genetically inactivated or activated β-catenin to determine its role in the pathogenesis of desmoplakin cardiomyopathy. Methods and results: The Dsp gene was conditionally deleted in the 2-week-old post-natal cardiac myocytes using tamoxifen-inducible MerCreMer mice (Myh6-McmTam:DspF/F). The cWNT/β-catenin pathway was markedly dysregulated in the Myh6-McmTam:DspF/F cardiac myocytes, as indicated by a concomitant increase in the expression of cWNT/β-catenin target genes, isoforms of its key co-effectors, and the inhibitors of the pathway. The β-catenin was inactivated or activated upon inducible deletion of its transcriptional or degron domain, respectively, in the Myh6-McmTam:DspF/F cardiac myocytes. Genetic inactivation of β-catenin in the Myh6-McmTam:DspF/F mice prolonged survival, improved cardiac function, reduced cardiac arrhythmias, and attenuated myocardial fibrosis, and cell death caused by apoptosis, necroptosis, and pyroptosis, i.e. PANoptosis. In contrast, activation of β-catenin had the opposite effects. The deleterious and the salubrious effects were independent of changes in the expression levels of the cWNT target genes and were associated with changes in several molecular and biological pathways, including cell death programmes. Conclusion: The cWNT/β-catenin was markedly dysregulated in the cardiac myocytes in a mouse model of desmoplakin cardiomyopathy. Inactivation of β-catenin attenuated, whereas its activation aggravated the phenotype, through multiple molecular pathways, independent of the cWNT transcriptional activity. Thus, suppression but not activation of β-catenin might be beneficial in desmoplakin cardiomyopathy.
MeSH term(s)	Mice ; Animals ; Arrhythmogenic Right Ventricular Dysplasia/genetics ; Desmoplakins/genetics ; Desmoplakins/metabolism ; beta Catenin/genetics ; beta Catenin/metabolism ; Cardiomyopathies/genetics ; Arrhythmias, Cardiac/metabolism ; Fibrosis
Chemical Substances	Desmoplakins ; beta Catenin
Language	English
Publishing date	2023-06-08
Publishing country	England
Document type	Journal Article ; Research Support, N.I.H., Extramural
ZDB-ID	80340-6
ISSN	1755-3245 ; 0008-6363
ISSN (online)	1755-3245
ISSN	0008-6363
DOI	10.1093/cvr/cvad137
Database	MEDical Literature Analysis and Retrieval System OnLINE

In stock of ZB MED Cologne/Königswinter

Zs.A 565: Show issues

Location:
Je nach Verfügbarkeit (siehe Angabe bei Bestand)
bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
Jg. 1995 - 2021: Lesesall (1.OG)
ab Jg. 2022: Lesesaal (EG)

Order via subito

Details ▾
- See ZB MED holdings
- Order with fees

Article ; Online: ClearF: a supervised feature scoring method to find biomarkers using class-wise embedding and reconstruction.

Wang, Sehee / Jeong, Hyun-Hwan / Sohn, Kyung-Ah

BMC medical genomics

2019 Volume 12, Issue Suppl 5, Page(s) 95

Abstract: Background: Feature selection or scoring methods for the detection of biomarkers are essential in bioinformatics. Various feature selection methods have been developed for the detection of biomarkers, and several studies have employed information- ... ...

Abstract	Background: Feature selection or scoring methods for the detection of biomarkers are essential in bioinformatics. Various feature selection methods have been developed for the detection of biomarkers, and several studies have employed information-theoretic approaches. However, most of these methods generally require a long processing time. In addition, information-theoretic methods discretize continuous features, which is a drawback that can lead to the loss of information. Results: In this paper, a novel supervised feature scoring method named ClearF is proposed. The proposed method is suitable for continuous-valued data, which is similar to the principle of feature selection using mutual information, with the added advantage of a reduced computation time. The proposed score calculation is motivated by the association between the reconstruction error and the information-theoretic measurement. Our method is based on class-wise low-dimensional embedding and the resulting reconstruction error. Given multi-class datasets such as a case-control study dataset, low-dimensional embedding is first applied to each class to obtain a compressed representation of the class, and also for the entire dataset. Reconstruction is then performed to calculate the error of each feature and the final score for each feature is defined in terms of the reconstruction errors. The correlation between the information theoretic measurement and the proposed method is demonstrated using a simulation. For performance validation, we compared the classification performance of the proposed method with those of various algorithms on benchmark datasets. Conclusions: The proposed method showed higher accuracy and lower execution time than the other established methods. Moreover, an experiment was conducted on the TCGA breast cancer dataset, and it was confirmed that the genes with the highest scores were highly associated with subtypes of breast cancer.
MeSH term(s)	Benchmarking ; Biomarkers/metabolism ; Computational Biology/methods ; Supervised Machine Learning
Chemical Substances	Biomarkers
Language	English
Publishing date	2019-07-11
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ISSN	1755-8794
ISSN (online)	1755-8794
DOI	10.1186/s12920-019-0512-9
Database	MEDical Literature Analysis and Retrieval System OnLINE

Order via subito

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Article ; Online: Topological integration of RPPA proteomic data with multi-omics data for survival prediction in breast cancer via pathway activity inference.

Kim, Tae Rim / Jeong, Hyun-Hwan / Sohn, Kyung-Ah

BMC medical genomics

2019 Volume 12, Issue Suppl 5, Page(s) 94

Abstract: Background: The analysis of integrated multi-omics data enables the identification of disease-related biomarkers that cannot be identified from a single omics profile. Although protein-level data reflects the cellular status of cancer tissue more ... ...

Abstract	Background: The analysis of integrated multi-omics data enables the identification of disease-related biomarkers that cannot be identified from a single omics profile. Although protein-level data reflects the cellular status of cancer tissue more directly than gene-level data, past studies have mainly focused on multi-omics integration using gene-level data as opposed to protein-level data. However, the use of protein-level data (such as mass spectrometry) in multi-omics integration has some limitations. For example, the correlation between the characteristics of gene-level data (such as mRNA) and protein-level data is weak, and it is difficult to detect low-abundance signaling proteins that are used to target cancer. The reverse phase protein array (RPPA) is a highly sensitive antibody-based quantification method for signaling proteins. However, the number of protein features in RPPA data is extremely low compared to the number of gene features in gene-level data. In this study, we present a new method for integrating RPPA profiles with RNA-Seq and DNA methylation profiles for survival prediction based on the integrative directed random walk (iDRW) framework proposed in our previous study. In the iDRW framework, each omics profile is merged into a single pathway profile that reflects the topological information of the pathway. In order to address the sparsity of RPPA profiles, we employ the random walk with restart (RWR) approach on the pathway network. Results: Our model was validated using survival prediction analysis for a breast cancer dataset from The Cancer Genome Atlas. Our proposed model exhibited improved performance compared with other methods that utilize pathway information and also out-performed models that did not include the RPPA data utilized in our study. The risk pathways identified for breast cancer in this study were closely related to well-known breast cancer risk pathways. Conclusions: Our results indicated that RPPA data is useful for survival prediction for breast cancer patients under our framework. We also observed that iDRW effectively integrates RNA-Seq, DNA methylation, and RPPA profiles, while variation in the composition of the omics data can affect both prediction performance and risk pathway identification. These results suggest that omics data composition is a critical parameter for iDRW.
MeSH term(s)	Breast Neoplasms/genetics ; Breast Neoplasms/metabolism ; DNA Methylation ; Humans ; Protein Array Analysis ; Proteomics ; Survival Analysis
Language	English
Publishing date	2019-07-11
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ISSN	1755-8794
ISSN (online)	1755-8794
DOI	10.1186/s12920-019-0511-x
Database	MEDical Literature Analysis and Retrieval System OnLINE

Order via subito

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

To top

More links

Kategorien

Order via subito

Inter-library loan at ZB MED

More links

Kategorien

In stock of ZB MED Cologne/Königswinter

Order via subito

More links

Kategorien

Order via subito

More links

Kategorien

Order via subito

More links

Kategorien

Order via subito

Inter-library loan at ZB MED

Full text online

More links

Kategorien

In stock of ZB MED Cologne/Königswinter

Order via subito

Full text online

More links

Kategorien

Inter-library loan at ZB MED

More links

Kategorien

In stock of ZB MED Cologne/Königswinter

Order via subito

More links

Kategorien

Order via subito

Inter-library loan at ZB MED

More links

Kategorien

Order via subito

Inter-library loan at ZB MED