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1.
Stud Health Technol Inform ; 267: 126-133, 2019 Sep 03.
Artigo em Inglês | MEDLINE | ID: mdl-31483264

RESUMO

Magnetic Resonance Fingerprinting (MRF) is an imaging technique acquiring unique time signals for different tissues. Although the acquisition is highly accelerated, the reconstruction time remains a problem, as the state-of-the-art template matching compares every signal with a set of possible signals. To overcome this limitation, deep learning based approaches, e.g. Convolutional Neural Networks (CNNs) have been proposed. In this work, we investigate the applicability of Recurrent Neural Networks (RNNs) for this reconstruction problem, as the signals are correlated in time. Compared to previous methods based on CNNs, RNN models yield significantly improved results using in-vivo data.


Assuntos
Algoritmos , Redes Neurais (Computação) , Bases de Dados Genéticas , Espectroscopia de Ressonância Magnética
2.
Medicine (Baltimore) ; 98(33): e16807, 2019 Aug.
Artigo em Inglês | MEDLINE | ID: mdl-31415393

RESUMO

BACKGROUND: Sepsis is a serious clinical condition with a poor prognosis, despite improvements in diagnosis and treatment.Therefore, novel biomarkers are necessary that can help with estimating prognosis and improving clinical outcomes of patients with sepsis. METHODS: The gene expression profiles GSE54514 and GSE63042 were downloaded from the GEO database. DEGs were screened by t test after logarithmization of raw data; then, the common DEGs between the 2 gene expression profiles were identified by up-regulation and down-regulation intersection. The DEGs were analyzed using bioinformatics, and a protein-protein interaction (PPI) survival network was constructed using STRING. Survival curves were constructed to explore the relationship between core genes and the prognosis of sepsis patients based on GSE54514 data. RESULTS: A total of 688 common DEGs were identified between survivors and non-survivors of sepsis, and 96 genes were involved in survival networks. The crucial genes Signal transducer and activator of transcription 5A (STAT5A), CCAAT/enhancer-binding protein beta (CEBPB), Myc proto-oncogene protein (MYC), and REL-associated protein (RELA) were identified and showed increased expression in sepsis survivors. These crucial genes had a positive correlation with patients' survival time according to the survival analysis. CONCLUSIONS: Our findings indicate that the genes STAT5A, CEBPB, MYC, and RELA may be important in predicting the prognosis of sepsis patients.


Assuntos
Proteína beta Intensificadora de Ligação a CCAAT/metabolismo , Proteínas Proto-Oncogênicas c-myc/metabolismo , Fator de Transcrição STAT5/metabolismo , Sepse/genética , Sepse/mortalidade , Fator de Transcrição RelA/metabolismo , Proteínas Supressoras de Tumor/metabolismo , Idoso , Idoso de 80 Anos ou mais , Biologia Computacional , Bases de Dados Genéticas , Regulação para Baixo , Feminino , Marcadores Genéticos , Humanos , Masculino , Pessoa de Meia-Idade , Prognóstico , Mapas de Interação de Proteínas , Fatores de Tempo , Transcriptoma , Regulação para Cima
3.
World J Microbiol Biotechnol ; 35(9): 139, 2019 Aug 26.
Artigo em Inglês | MEDLINE | ID: mdl-31451943

RESUMO

Exploitation of microbes, especially fungi, has the potential to help humankind meet the UN's sustainable development goals, help feed the worlds growing population and improve bioeconomies of poorer nations. The majority of the world's fungal genetic resources are held in collections in developed countries, primarily within the USA, Europe and Japan. Very little capacity exists in low to middle income countries, which are often rich in biodiversity but lack resources to be able to conserve and exploit their own microbial resources. In this paper we review the current challenges facing culture collections and the challenges of integrating new approaches, the worth of collaborative networks, and the importance of technology, taxonomy and data handling. We address the need to underpin research and development in developing countries through the need to build 'in country' infrastructure to address these challenges, whilst tackling the global challenges to meet the requirements of the research community through the impacts of legislation and the Nagoya protocol on access to biological resources.


Assuntos
Fungos , Desenvolvimento Sustentável/tendências , Biodiversidade , Bases de Dados Genéticas , Fungos/classificação , Fungos/genética , Fungos/isolamento & purificação , Fungos/fisiologia , Disseminação de Informação , Internacionalidade
4.
Stud Health Technol Inform ; 266: 76-82, 2019 Aug 08.
Artigo em Inglês | MEDLINE | ID: mdl-31397305

RESUMO

SRA, NCBI's Sequence Read Archive, is a valuable resource holding a near definitive collection of the world's collective sequenced reads for academic purposes. Increasingly, these reads are being used for both basic research and clinical investigations. When time is a critical factor in analysis, such as during bacterial outbreaks, the geographical separation between Australia and the offshore NCBI SRA servers can result in significant delays that may have adverse clinical outcomes. To address this, Queensland Genomics commissioned a pilot program for the establishment of a local Australian SRA Cache. Utilizing the hosting capabilities of the NeCTAR Research Cloud, QRIScloud's HTC infrastructure and the MeDiCI data fabric as a storage solution, and the software stack of Cromwell for workflow management, PostgreSQL database for sample and job metadata, and a coordinator Python Flask application, a local cache of seventeen bacterial species was established. Furthermore, the workflow capabilities of Cromwell were leveraged to provide analysis solutions for cached sample data, including quality control and taxonomic profiling, and individual and multiple sample analysis. Moving forward to a broader rollout of increased bacterial species, it was found that the initial storage estimation did not keep up with the exponential increase sequencing reads uploaded to NCBI SRA, which while highlighting the increasing availability and importance in modern research, will need to be addressed.


Assuntos
Bases de Dados Genéticas , Software , Austrália , Genômica , Queensland
5.
Stud Health Technol Inform ; 264: 1610-1611, 2019 Aug 21.
Artigo em Inglês | MEDLINE | ID: mdl-31438256

RESUMO

Recently, there has been an increasing interest in mining time series databases with a focus on data representation. We propose a hybrid statistical and temporal logic model to yield search pattern that can be used for pattern matching and database search to identify novel and common patterns in temporal expression experiments. The method accounts for various challenges that can be found in publicly available gene expression databases.


Assuntos
Perfilação da Expressão Gênica , Algoritmos , Bases de Dados Factuais , Bases de Dados Genéticas
6.
Yi Chuan ; 41(8): 746-753, 2019 Aug 20.
Artigo em Chinês | MEDLINE | ID: mdl-31447425

RESUMO

Personal genomic information benefits from accumulated big data and its application is no longer limited to scientific research. Presently, it is undergoing the transformation to daily medical practice. Systematic arrangement, archiving and rational utilization of disease-related genomic information is an important foundation of future precision medicine. Hemoglobinopathy is prevalent in southern China, but its molecular pathological basis has racial specificity. To facilitate clinical diagnosis and genetic screening of hemoglobinopathy in southern China, we established the LOVD gene data management system for the variation and phenotype spectrum of hemoglobinopathy. Then we designed an integrated and efficient on-line auxiliary accurate diagnosis and risk assessment system in order to assist clinicians to make comprehensive diagnosis and genetic counseling in a short time based on cloud standardized annotated library of specific hemoglobinopathy variants and diagnostic repository. The methodology and experience of improving the clinical decision-making efficiency of diseases with big data and artificial intelligence technology can be used as an example in the clinical and preventive application of other diseases.


Assuntos
Bases de Dados Genéticas , Sistemas de Apoio a Decisões Clínicas , Hemoglobinopatias/genética , Mutação , China , Aconselhamento Genético , Testes Genéticos , Humanos
7.
Yi Chuan ; 41(8): 761-772, 2019 Aug 20.
Artigo em Chinês | MEDLINE | ID: mdl-31447427

RESUMO

Genetic resources are important national strategic resources. Their preservation, protection and rational utilization form a solid foundation to guarantee national security and to build national competitiveness for the future. Due to a relatively late starting point, China is actively catching up with global peers in storing genetic samples and data. In view of this, in 2011 China approved a plan to build its first nation-level comprehensive gene bank, the China National GeneBank (CNGB), and entrusted BGI-Research to implement its construction and operation. It is China's first gene bank for "reading, writing and storing" bioresources. In this paper, we summarize the development of influential platforms at home and abroad, and focus on CNGB's position, mission, and its structure of "Three Banks and Two Platforms". CNGB launched its official operation in September 2016 and aims to develop a world-class, non-profit and strategic platform that supports science and technology development. It has built capacities to store tens of millions of traceable samples and to analyze handreds of thousanda of WGS each year. It has also set up China's first Pb-level digitalization platform and a high-efficient synthesis platform with a production rate of ten million bases per year. Based on such capacities, CNGB has established its open sharing mechanism for biological samples and data, provided public platform services for life science research, and achieved initial results in supporting innovation and development of the bio-industry.


Assuntos
Bases de Dados Genéticas , Pesquisa , China , Disseminação de Informação
8.
BMC Genomics ; 20(Suppl 3): 295, 2019 05 08.
Artigo em Inglês | MEDLINE | ID: mdl-31284879

RESUMO

BACKGROUND: Mitochondria is a powerhouse of all eukaryotic cells that have its own circular DNA (mtDNA) encoding various RNAs and proteins. Somatic perturbations of mtDNA are accumulating with age thus it is of great importance to uncover the main sources of mtDNA instability. Recent analyses demonstrated that somatic mtDNA deletions depend on imperfect repeats of various nature between distant mtDNA segments. However, till now there are no comprehensive databases annotating all types of imperfect repeats in numerous species with sequenced complete mitochondrial genome as well as there are no algorithms capable to call all types of imperfect repeats in circular mtDNA. RESULTS: We implemented naïve algorithm of pattern recognition by analogy to standard dot-plot construction procedures allowing us to find both perfect and imperfect repeats of four main types: direct, inverted, mirror and complementary. Our algorithm is adapted to specific characteristics of mtDNA such as circularity and an excess of short repeats - it calls imperfect repeats starting from the length of 10 b.p. We constructed interactive web available database ImtRDB depositing perfect and imperfect repeats positions in mtDNAs of more than 3500 Vertebrate species. Additional tools, such as visualization of repeats within a genome, comparison of repeat densities among different genomes and a possibility to download all results make this database useful for many biologists. Our first analyses of the database demonstrated that mtDNA imperfect repeats (i) are usually short; (ii) associated with unfolded DNA structures; (iii) four types of repeats positively correlate with each other forming two equivalent pairs: direct and mirror versus inverted and complementary, with identical nucleotide content and similar distribution between species; (iv) abundance of repeats is negatively associated with GC content; (v) dinucleotides GC versus CG are overrepresented on light chain of mtDNA covered by repeats. CONCLUSIONS: ImtRDB is available at http://bioinfodbs.kantiana.ru/ImtRDB/ . It is accompanied by the software calling all types of interspersed repeats with different level of degeneracy in circular DNA. This database and software can become a very useful tool in various areas of mitochondrial and chloroplast DNA research.


Assuntos
DNA Mitocondrial/genética , Bases de Dados Genéticas , Sequências Repetitivas de Ácido Nucleico , Software , Algoritmos , DNA Circular/genética
9.
Medicine (Baltimore) ; 98(27): e16240, 2019 Jul.
Artigo em Inglês | MEDLINE | ID: mdl-31277141

RESUMO

Osteoarthritis (OA), also known as degenerative arthritis, affects millions of people all over the world. OA occurs when the cartilage wears down over time, which is a worldwide complaint. The aim of this study was to screen and verify hub genes involved in developmental chondrogenesis as well as to explore potential molecular mechanisms.The expression profiles of GSE51812 were downloaded from the Gene Expression Omnibus (GEO) database, which contained 9 samples, including 6-week pre-chondrocytes (PC, 6 independent specimens) and 17-week fetal periarticular resting chondrocytes (RC, 3 independent specimens). The raw data were integrated to obtain differentially expressed genes (DEGs) and were further analyzed with bioinformatics analysis. The Gene Ontology (GO) and pathway enrichment of DEGs were conducted via Database for Annotation, Visualization, and Integrated Discovery (DAVID). The protein-protein interaction (PPI) networks of the DEGs were constructed based on data from the search tool for the retrieval of interacting genes (STRING) database. An intersection figure was provided to show the relationship between the DEGs identified in this study and genes from any existed related studies.A total of 9486 DEGs, including 4821 upregulated genes and 4665 downregulated genes were observed. The top 30 developmental chondrogenesis associated genes were identified, including matrix metalloproteinase (MMP)1, MMP3, MMP13, prostaglandin-endoperoxide synthase 2 (PTGS2), and so on. The majority of DEGs, including PTGS2, CCL20, CHI3L1, LIF, CXCL8, and CXCL12 were intensively enriched in immune-associated biological process terms, including inflammatory, and immune responses. Additionally, the majority of DEGs were mainly enriched in NF-kappa ß (NF-kß) signaling pathway and tumor necrosis factor (TNF) signaling pathway. The hub genes identified in STRING and Cytoscape databases included MMP1, MMP3, MMP13, PTGS2 and so on. Among the top 30 upregulated and downregulated DEGs, there were 15 genes have been reported to be associated with OA or developmental chondrogenesis.This large scale gene expression study observed genes associated with human developmental chondrogenesis and their relative GO function, which may offer opportunities for the research for cartilage tissue engineering and novel insights into the prevention of OA in the near future.


Assuntos
Condrogênese/genética , Biologia Computacional/métodos , Perfilação da Expressão Gênica/métodos , Regulação da Expressão Gênica , Osteoartrite/genética , Biomarcadores/metabolismo , Bases de Dados Genéticas , Ontologia Genética , Redes Reguladoras de Genes , Humanos , Osteoartrite/patologia , Transdução de Sinais
10.
Medicine (Baltimore) ; 98(27): e16269, 2019 Jul.
Artigo em Inglês | MEDLINE | ID: mdl-31277149

RESUMO

Esophageal squamous cell carcinoma (ESCC) is a malignancy that severely threatens human health and carries a high incidence rate and a low 5-year survival rate. MicroRNAs (miRNAs) are commonly accepted as a key regulatory function in human cancer, but the potential regulatory mechanisms of miRNA-mRNA related to ESCC remain poorly understood.The GSE55857, GSE43732, and GSE6188 miRNA microarray datasets and the gene expression microarray datasets GSE70409, GSE29001, and GSE20347 were downloaded from Gene Expression Omnibus databases. The differentially expressed miRNAs (DEMs) and differentially expressed genes (DEGs) were obtained using GEO2R. Gene ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis for DEGs were performed by Database for Annotation, Visualization and Integrated Discovery (DAVID). A protein-protein interaction (PPI) network and functional modules were established using the STRING database and were visualized by Cytoscape. Kaplan-Meier analysis was constructed based on The Cancer Genome Atlas (TCGA) database.In total, 26 DEMs and 280 DEGs that consisted of 96 upregulated and 184 downregulated genes were screened out. A functional enrichment analysis showed that the DEGs were mainly enriched in the ECM-receptor interaction and cytochrome P450 metabolic pathways. In addition, MMP9, PCNA, TOP2A, MMP1, AURKA, MCM2, IVL, CYP2E1, SPRR3, FOS, FLG, TGM1, and CYP2C9 were considered to be hub genes owing to high degrees in the PPI network. MiR-183-5p was with the highest connectivity target genes in hub genes. FOS was predicted to be a common target gene of the significant DEMs. Hsa-miR-9-3p, hsa-miR-34c-3p and FOS were related to patient prognosis and higher expression of the transcripts were associated with a poor OS in patients with ESCC.Our study revealed the miRNA-mediated hub genes regulatory network as a model for predicting the molecular mechanism of ESCC. This may provide novel insights for unraveling the pathogenesis of ESCC.


Assuntos
Biologia Computacional/métodos , Neoplasias Esofágicas/genética , Carcinoma de Células Escamosas do Esôfago/genética , Perfilação da Expressão Gênica/métodos , Regulação Neoplásica da Expressão Gênica , MicroRNAs/genética , RNA Neoplásico/genética , Bases de Dados Genéticas , Neoplasias Esofágicas/metabolismo , Carcinoma de Células Escamosas do Esôfago/metabolismo , Ontologia Genética , Redes Reguladoras de Genes , Humanos , Análise em Microsséries
12.
Zhonghua Liu Xing Bing Xue Za Zhi ; 40(7): 805-809, 2019 Jul 10.
Artigo em Chinês | MEDLINE | ID: mdl-31357803

RESUMO

Objective: To explore an effective long non-coding RNA (lncRNA) signature in predicting the prognosis of hepatocellular carcinoma through the analysis on RNA sequencing data of hepatocellular carcinoma patients and peritumoral tissues in the Cancer Genome Atlas (TCGA) database. Methods: The clinical characteristics and RNA sequencing data of 377 hepatocellular carcinoma patients were obtained from TCGA database by the end of February 2018. Then, differentially expressed lncRNAs between 50 pairs of tumor and peritumoral tissues were explored using student's t-test. Next, a lncRNA signature was established through LASSO Cox regression analysis. All the patients were divided into four groups (

Assuntos
Carcinoma Hepatocelular/genética , Neoplasias Hepáticas/genética , RNA Longo não Codificante , Carcinoma Hepatocelular/terapia , Bases de Dados Genéticas , Humanos , Neoplasias Hepáticas/terapia , Prognóstico
13.
Nat Commun ; 10(1): 2933, 2019 07 03.
Artigo em Inglês | MEDLINE | ID: mdl-31270330

RESUMO

Synthetic DNA is becoming an attractive substrate for digital data storage due to its density, durability, and relevance in biological research. A major challenge in making DNA data storage a reality is that reading DNA back into data using sequencing by synthesis remains a laborious, slow and expensive process. Here, we demonstrate successful decoding of 1.67 megabytes of information stored in short fragments of synthetic DNA using a portable nanopore sequencing platform. We design and validate an assembly strategy for DNA storage that drastically increases the throughput of nanopore sequencing. Importantly, this assembly strategy is generalizable to any application that requires nanopore sequencing of small DNA amplicons.


Assuntos
DNA/genética , Armazenamento e Recuperação da Informação/métodos , DNA/síntese química , Bases de Dados Genéticas , Nanoporos , Nanotecnologia , Análise de Sequência de DNA/instrumentação
14.
BMC Bioinformatics ; 20(1): 373, 2019 Jul 03.
Artigo em Inglês | MEDLINE | ID: mdl-31269893

RESUMO

BACKGROUND: RNA molecules play many crucial roles in living systems. The spatial complexity that exists in RNA structures determines their cellular functions. Therefore, understanding RNA folding conformations, in particular, RNA secondary structures, is critical for elucidating biological functions. Existing literature has focused on RNA design as either an RNA structure prediction problem or an RNA inverse folding problem where free energy has played a key role. RESULTS: In this research, we propose a Positive-Unlabeled data- driven framework termed ENTRNA. Other than free energy and commonly studied sequence and structural features, we propose a new feature, Sequence Segment Entropy (SSE), to measure the diversity of RNA sequences. ENTRNA is trained and cross-validated using 1024 pseudoknot-free RNAs and 1060 pseudoknotted RNAs from the RNASTRAND database respectively. To test the robustness of the ENTRNA, the models are further blind tested on 206 pseudoknot-free and 93 pseudoknotted RNAs from the PDB database. For pseudoknot-free RNAs, ENTRNA has 86.5% sensitivity on the training dataset and 80.6% sensitivity on the testing dataset. For pseudoknotted RNAs, ENTRNA shows 81.5% sensitivity on the training dataset and 71.0% on the testing dataset. To test the applicability of ENTRNA to long structural-complex RNA, we collect 5 laboratory synthetic RNAs ranging from 1618 to 1790 nucleotides. ENTRNA is able to predict the foldability of 4 RNAs. CONCLUSION: In this article, we reformulate the RNA design problem as a foldability prediction problem which is to predict the likelihood of the co-existence of a sequence-structure pair. This new construct has the potential for both RNA structure prediction and the inverse folding problem. In addition, this new construct enables us to explore data-driven approaches in RNA research.


Assuntos
Algoritmos , RNA/metabolismo , Bases de Dados Genéticas , RNA/química , Dobramento de RNA , Termodinâmica
15.
Adv Exp Med Biol ; 1166: 57-74, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-31301046

RESUMO

Epigenetic information refers to heritable changes in gene expression that occur without modifications at the DNA sequence level. These changes are orchestrated by different epigenetic mechanisms such as DNA methylation, posttranslational modifications of histones, and the presence of noncoding RNAs. Epigenetic information regulates chromatin structure to confer cell-specific gene expression.The sperm epigenome is the result of three periods of global resetting during men's life. Germ cell epigenome reprogramming is designed to allow cell totipotency and to prevent the transmission of epimutations via spermatozoa. At the end of these reprogramming events, the sperm epigenome has a very specific epigenetic pattern that is a footprint of past reprogramming events and has an influence on embryo development.Several data demonstrate that not all regions of the epigenome are erased during the reprogramming periods, suggesting the transmission of epigenetic information from fathers to offspring via spermatozoa. Moreover, it is becoming increasingly clear that the sperm epigenome is sensitive to environmental factors during the process of gamete differentiation, suggesting the plasticity of the sperm epigenetic signature according to the circumstances of the individual's life.In this chapter, we provided strong evidences about the association between variations of the sperm epigenome and the exposure to environmental factors. Moreover, we will present data about how epigenetic mechanisms are candidates for transferring paternal environmental information to offspring.


Assuntos
Exposição Ambiental , Epigênese Genética , Padrões de Herança , Metilação de DNA , Bases de Dados Genéticas , Epigenômica , Variação Genética , Células Germinativas , Humanos , Padrões de Herança/genética , Masculino
16.
BMC Bioinformatics ; 20(1): 399, 2019 Jul 18.
Artigo em Inglês | MEDLINE | ID: mdl-31319812

RESUMO

BACKGROUND: High-throughput experiments can bring to light associations between genes, proteins and/or metabolites, many of which will be explainable by existing knowledge. Our aim is to speed elucidation of such explanations and, in some cases, find explanations that scientists might otherwise overlook. RESULTS: We describe the MultiOmics Explainer, a new tool within the Pathway Tools software suite that leverages what is known about an organism's metabolic and regulatory network to suggest explanations for the results of omics experiments. Querying a database such as EcoCyc, the MultiOmics Explainer searches the organism's network of metabolic reactions, transporters, cofactors, enzyme substrate-level activation and inhibition relationships, and transcriptional and translational regulation relationships to identify paths of influence among input genes, proteins and metabolites. Results are presented in a combined metabolic and regulatory diagram. We present several examples of explanations generated for associations found in the Escherichia coli literature. CONCLUSIONS: The MultiOmics Explainer is a valuable tool that helps researchers understand and interpret the results of their omics experiments in the context of what is known about an organism's metabolic and regulatory network. It showcases the rich set of computational inferences that can be drawn from a database such as EcoCyc that encodes a diverse range of biological interactions.


Assuntos
Perfilação da Expressão Gênica , Metabolômica , Proteômica , Software , Bases de Dados Factuais , Bases de Dados Genéticas , Escherichia coli/genética , Escherichia coli/metabolismo , Genoma , Redes e Vias Metabólicas
17.
BMC Bioinformatics ; 20(1): 401, 2019 Jul 19.
Artigo em Inglês | MEDLINE | ID: mdl-31324140

RESUMO

BACKGROUND: Visualization tools for deep learning models typically focus on discovering key input features without considering how such low level features are combined in intermediate layers to make decisions. Moreover, many of these methods examine a network's response to specific input examples that may be insufficient to reveal the complexity of model decision making. RESULTS: We present DeepResolve, an analysis framework for deep convolutional models of genome function that visualizes how input features contribute individually and combinatorially to network decisions. Unlike other methods, DeepResolve does not depend upon the analysis of a predefined set of inputs. Rather, it uses gradient ascent to stochastically explore intermediate feature maps to 1) discover important features, 2) visualize their contribution and interaction patterns, and 3) analyze feature sharing across tasks that suggests shared biological mechanism. We demonstrate the visualization of decision making using our proposed method on deep neural networks trained on both experimental and synthetic data. DeepResolve is competitive with existing visualization tools in discovering key sequence features, and identifies certain negative features and non-additive feature interactions that are not easily observed with existing tools. It also recovers similarities between poorly correlated classes which are not observed by traditional methods. DeepResolve reveals that DeepSEA's learned decision structure is shared across genome annotations including histone marks, DNase hypersensitivity, and transcription factor binding. We identify groups of TFs that suggest known shared biological mechanism, and recover correlation between DNA hypersensitivities and TF/Chromatin marks. CONCLUSIONS: DeepResolve is capable of visualizing complex feature contribution patterns and feature interactions that contribute to decision making in genomic deep convolutional networks. It also recovers feature sharing and class similarities which suggest interesting biological mechanisms. DeepResolve is compatible with existing visualization tools and provides complementary insights.


Assuntos
Algoritmos , Aprendizado Profundo , Genômica , Redes Neurais (Computação) , Sequência de Bases , Bases de Dados Genéticas , Código das Histonas , Histonas/metabolismo , Fatores de Transcrição/metabolismo
18.
BMC Bioinformatics ; 20(1): 404, 2019 Jul 25.
Artigo em Inglês | MEDLINE | ID: mdl-31345171

RESUMO

BACKGROUND: It has been shown that the deregulation of miRNAs is associated with the development and progression of many human diseases. To reduce time and cost of biological experiments, a number of algorithms have been proposed for predicting miRNA-disease associations. However, the existing methods rarely investigated the cause-and-effect mechanism behind these associations, which hindered further biomedical follow-ups. RESULTS: In this study, we presented a CCA-based model in which the possible molecular causes of miRNA-disease associations were comprehensively revealed by extracting correlated sets of genes and diseases based on the co-occurrence of miRNAs in target gene profiles and disease profiles. Our method directly suggested the underlying genes involved, which could be used for experimental tests and confirmation. The inference of associated diseases of a new miRNA was made by taking into account the weight vectors of the extracted sets. We extracted 60 pairs of correlated sets from 404 miRNAs with two profiles for 2796 target genes and 362 diseases. The extracted diseases could be considered as possible outcomes of miRNAs regulating the target genes which appeared in the same set, some of which were supported by independent source of information. Furthermore, we tested our method on the 404 miRNAs under the condition of 5-fold cross validations and received an AUC value of 0.84606. Finally, we extensively inferred miRNA-disease associations for 100 new miRNAs and some interesting prediction results were validated by established databases. CONCLUSIONS: The encouraging results demonstrated that our method could provide a biologically relevant prediction and interpretation of associations between miRNAs and diseases, which were of great usefulness when guiding biological experiments for scientific research.


Assuntos
Algoritmos , Biologia Computacional/métodos , Doença/genética , Estudos de Associação Genética , MicroRNAs/genética , Bases de Dados Genéticas , Humanos , MicroRNAs/metabolismo , Modelos Genéticos
19.
Biochim Biophys Acta Rev Cancer ; 1872(1): 122-137, 2019 08.
Artigo em Inglês | MEDLINE | ID: mdl-31265877

RESUMO

The rapid evolution of next-generation sequencing (NGS)-based tumor genomic profile detection and the emergence of molecularly targeted therapies have enabled precision oncology. In NGS-based analysis, various types of databases have been developed to perform different functions. However, many problems still exist when using these public databases. Therefore, it is important to better understand the characteristics and limitations of each database and have them complement each other to provide useful clinical evidence for NGS testing. In this review, we elaborate on the important role of databases and their concrete applications in NGS-based somatic mutation detection. We introduce the typically used databases for sequence alignment, variant filtration, and variant interpretation, and compare the differences between the databases with similar functions. Subsequently, we determine the limitations of each database and provide the corresponding solutions. Furthermore, we present an overview diagram to clearly illustrate the database used in the entire NGS-based somatic mutation detection pipeline.


Assuntos
Análise Mutacional de DNA , Bases de Dados Genéticas , Sequenciamento de Nucleotídeos em Larga Escala/métodos , Neoplasias/genética , Genoma Humano/genética , Humanos , Mutação , Medicina de Precisão , Análise de Sequência de DNA/métodos
20.
Hum Genet ; 138(10): 1155-1169, 2019 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-31342140

RESUMO

Vitamin D inadequacy, assessed by 25-hydroxyvitamin D [25(OH)D], affects around 50% of adults in the United States and is associated with numerous adverse health outcomes. Blood 25(OH)D concentrations are influenced by genetic factors that may determine how much vitamin D intake is required to reach optimal 25(OH)D. Despite large genome-wide association studies (GWASs), only a small portion of the genetic factors contributing to differences in 25(OH)D has been discovered. Therefore, knowledge of a fuller set of genetic factors could be useful for risk prediction of 25(OH)D inadequacy, personalized vitamin D supplementation, and prevention of downstream morbidity and mortality. Using PRSice and weights from published African- and European-ancestry GWAS summary statistics, ancestry-specific polygenic scores (PGSs) were created to capture a more complete set of genetic factors in those of European (n = 9569) or African ancestry (n = 2761) from three cohort studies. The PGS for African ancestry was derived using all input SNPs (a p value cutoff of 1.0) and had an R2 of 0.3%; for European ancestry, the optimal PGS used a p value cutoff of 3.5 × 10-4 in the target/tuning dataset and had an R2 of 1.0% in the validation cohort. Those with highest genetic risk had 25(OH)D that was 2.8-3.0 ng/mL lower than those with lowest genetic risk (p = 0.0463-3.2 × 10-13), requiring an additional 467-500 IU of vitamin D intake to maintain equivalent 25(OH)D. PGSs are a powerful predictive tool that could be leveraged for personalized vitamin D supplementation to prevent the negative downstream effects of 25(OH)D inadequacy.


Assuntos
Grupo com Ancestrais do Continente Africano/genética , Grupo com Ancestrais do Continente Europeu/genética , Genética Populacional , Padrões de Herança , Herança Multifatorial , Polimorfismo de Nucleotídeo Único , Vitamina D/análogos & derivados , Estudos de Coortes , Bases de Dados Genéticas , Suplementos Nutricionais , Feminino , Estudo de Associação Genômica Ampla , Humanos , Masculino , Pessoa de Meia-Idade , Raios Ultravioleta , Vitamina D/sangue
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