Finding your Way Through Pneumocystis Sequences in the NCBI Gene Database

2014 ◽  
Vol 61 (5) ◽  
pp. 537-555 ◽  
Author(s):  
Christiane Weissenbacher-Lang ◽  
Nora Nedorost ◽  
Herbert Weissenböck
Keyword(s):  
Gene Database ◽  
Ncbi Gene Database

scholarly journals Genotyping of the EIF1AY Gene in Iranian Patients with Non-Obstructive Azoospermia

2019 ◽  
Vol 13 (1) ◽  
pp. 46-50
Author(s):  
Elham Yarahmadi ◽  
Parnaz Borjian Boroujeni ◽  
Mehdi Totonchi ◽  
Hamid Gourabi
Keyword(s):  
Control Group ◽  
Case Group ◽  
Obstructive Azoospermia ◽  
Nucleotide Variation ◽  
Single Nucleotide ◽  
Significant Difference ◽  
Gene Database ◽  
Normal Spermatogenesis ◽  
Single Nucleotide Variations ◽  
Ncbi Gene Database

Background: EIF1AY is one of the genes essential for normal spermatogenesis and is located in azoospermic factors region. Objective: The present study was designed to investigate the EIF1AY gene nucleotide variations, and correlate it with spermatogenic maturation arrest and azoospermia in Iranian population. Methods: A total number of 30 Iranian idiopathic non-obstructive azoospermic patients were selected as case group and 30 fertile men served as a control group who had at least 1 child. Nucleotide variation was analyzed in exon 3 and exon 5 in EIF1AY gene of both groups. DNA extraction from peripheral blood samples of selected individuals was done followed by amplification by PCR and sequencing with Sangar method. Results: Totally 3 single nucleotide variations were identified: one in the intronic region of exon 3, next one in non-coding transcript exon variant (rs13447352) and the third one in the exonic region of exon 5, all were registered in NCBI-Gene database. Conclusion: There was no statistically significant difference in the incidence of nucleotide variation between 2 study populations (p > 0.05). Further studies are required to specify the effects of Y: T20588295G variation on modification of protein structure, as well as the expression pattern of the gene and its association with azoospermia.

scholarly journals Potential Key Genes Associated with Stroke types and its subtypes: A Computational Approach

2021 ◽  
Author(s):  
Gourab Das ◽  
Pradeep Kumar
Keyword(s):  
Stroke Risk ◽  
Diagnostic Marker ◽  
Small Vessel Disease ◽  
Large Artery ◽  
Human Genes ◽  
Gene Database ◽  
Key Genes ◽  
Toast Classification ◽  
Ncbi Gene Database ◽  
Gene Symbols

AbstractTo investigate prospective key genes and pathways associated with the pathogenesis and prognosis of stroke types along with subtypes. Human genes using genome assembly build 38 patch release 13 with known gene symbols through NCBI gene database (https://www.ncbi.nlm.nih.gov/gene) were fetched. PubMed advanced queries were constructed using stroke-related keywords and associations were calculated using Normalized pointwise mutual information (nPMI) between each gene symbol and queries. Genes related with stroke risk within their types and subtypes were investigated in order to discover genetic markers to predict individuals who are at the risk of developing stroke with their subtypes. A total of 2,785 (9.4%) genes were found to be linked to the risk of stroke. Based on stroke types, 1,287 (46.2%) and 376 (13.5%) genes were found to be related with IS and HS respectively. Further stratification of IS based on TOAST classification, 86 (6.6%) genes were confined to Large artery atherosclerosis; 131 (10.1%) and 130 (10%) genes were related with the risk of small vessel disease and Cardioembolism subtypes of IS. Besides, a prognostic panel of 9 genes signature consisting of CYP4A11, ALOX5P, NOTCH, NINJ2, FGB, MTHFR, PDE4D, HDAC9, and ZHFX3 can be treated as a diagnostic marker to predict individuals who are at the risk of developing stroke with their subtypes.

scholarly journals Anti-inflammatory Mechanism of Rhein in Treating Asthma Based on Network Pharmacology

2020 ◽  
Author(s):  
Junfang Feng ◽  
Ou Chen ◽  
Yibiao Wang
Keyword(s):  
Network Pharmacology ◽  
Ppi Network ◽  
Operational Mechanism ◽  
Inflammatory Mechanism ◽  
Response Network ◽  
Target Network ◽  
Gene Database ◽  
Anti Inflammatory ◽  
Ncbi Gene Database ◽  
Network Software

Abstract BackgroundNetwork pharmacology was used to study Rhein -target-pathway and to clarify its anti-inflammatory mechanism in the treatment of asthma.and provide a new idea for the treatment of asthmaMethodsThis method, which allows using network pharmacology to figure out the operational mechanism of Rhein-Target-Pathway, defines the effect of anti-inflammatory in treating asthma. The platform of Traditional Chinese Medicine Molecular Mechanism Bioinformatics, a web server for network, is used to get the corresponding target of Rhein and permit molecular docking. Cytoscape3.7.1, a kind of network software, is used to construct Rhein-predicted target network and analyse network topology. Search anti-inflammatory targets in the database of TTD and then construct the PPI network as well as create protein interaction networks that are combined with the Rhein-predicted target network. The anti-inflammatory targets of Rhein should be presented. The asthma genes of human being can be attained from the database of NCBI Gene Database and construct correspondence vivo response network model. Find Anti-inflammatory targets of Rhein against asthma, screen anti-inflammatory targets of Rhein related with Pathogenesis of asthma. Enrichr database is used to analyse signal pathway from anti-inflammatory targets of Rhein KEGG.ResultsAccording to the study, Rhein corresponds to 17 target proteins, four anti-inflammatory targets of Rhein related to asthma(MAPK14, EGFR, ERBB2, TNFRSF1A) are probably the most important targets where asthma is treated by Rhein.ConclusionsThese four anti-inflammatory targets of Rhein related to asthma are probably the key targets in the treatment of asthma by using Rhein. For the purpose of preventing the occurrence as well as development of asthma and delaying the progress of the disease, one or some of the four anti-inflammatory targets of Rhein related to asthma can be controlled.

scholarly journals InvasionDB: A genome and gene database of invasive alien species

2021 ◽  
Vol 20 (1) ◽  
pp. 191-200
Author(s):  
Cong HUANG ◽  
Kun LANG ◽  
Wan-qiang QIAN ◽  
Shu-ping WANG ◽  
Xiao-mei CAO ◽  
...  
Keyword(s):  
Alien Species ◽  
Invasive Alien Species ◽  
A Genome ◽  
Gene Database

scholarly journals Online database for brain cancer-implicated genes: exploring the subtype-specific mechanisms of brain cancer

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Min Zhao ◽  
Yining Liu ◽  
Guiqiong Ding ◽  
Dacheng Qu ◽  
Hong Qu
Keyword(s):  
Brain Cancer ◽  
Differential Expression Analysis ◽  
Survival Rates ◽  
Brain Regions ◽  
Solid Base ◽  
Cancer Subtypes ◽  
Human Genes ◽  
Subtype Identification ◽  
Genetic Mechanisms ◽  
Gene Database

Abstract Background Brain cancer is one of the eight most common cancers occurring in people aged 40+ and is the fifth-leading cause of cancer-related deaths for males aged 40–59. Accurate subtype identification is crucial for precise therapeutic treatment, which largely depends on understanding the biological pathways and regulatory mechanisms associated with different brain cancer subtypes. Unfortunately, the subtype-implicated genes that have been identified are scattered in thousands of published studies. So, systematic literature curation and cross-validation could provide a solid base for comparative genetic studies about major subtypes. Results Here, we constructed a literature-based brain cancer gene database (BCGene). In the current release, we have a collection of 1421 unique human genes gathered through an extensive manual examination of over 6000 PubMed abstracts. We comprehensively annotated those curated genes to facilitate biological pathway identification, cancer genomic comparison, and differential expression analysis in various anatomical brain regions. By curating cancer subtypes from the literature, our database provides a basis for exploring the common and unique genetic mechanisms among 40 brain cancer subtypes. By further prioritizing the relative importance of those curated genes in the development of brain cancer, we identified 33 top-ranked genes with evidence mentioned only once in the literature, which were significantly associated with survival rates in a combined dataset of 2997 brain cancer cases. Conclusion BCGene provides a useful tool for exploring the genetic mechanisms of and gene priorities in brain cancer. BCGene is freely available to academic users at http://soft.bioinfo-minzhao.org/bcgene/.

scholarly journals SAGD: a comprehensive sex-associated gene database from transcriptomes

2018 ◽  
Vol 47 (D1) ◽  
pp. D835-D840 ◽  
Author(s):  
Meng-Wei Shi ◽  
Na-An Zhang ◽  
Chuan-Ping Shi ◽  
Chun-Jie Liu ◽  
Zhi-Hui Luo ◽  
...  
Keyword(s):  
Gene Database

Analysis of the mechanism in salivary gland development using gene database

2018 ◽  
Vol 60 (4) ◽  
pp. 83-86 ◽  
Author(s):  
Takayoshi Sakai ◽  
Hitomi Ono Minagi ◽  
Aya Obana-Koshino ◽  
Manabu Sakai
Keyword(s):  
Salivary Gland ◽  
Gene Database ◽  
Gland Development

A community-supported metaproteomic pipeline for improving peptide identifications in hydrothermal vent microbiota

2021 ◽  
Author(s):  
Yafei Chang ◽  
Qilian Fan ◽  
Jialin Hou ◽  
Yu Zhang ◽  
Jing Li
Keyword(s):  
Deep Sea ◽  
Hydrothermal Vent ◽  
Hydrothermal Vents ◽  
Extreme Environments ◽  
Reference Database ◽  
False Discovery Rate Method ◽  
Analysis Strategy ◽  
Gene Database ◽  
And Function ◽  
Functional Profiles

Abstract Microorganisms in deep-sea hydrothermal vents provide valuable insights into life under extreme conditions. Mass spectrometry-based proteomics has been widely used to identify protein expression and function. However, the metaproteomic studies in deep-sea microbiota have been constrained largely by the low identification rates of protein or peptide. To improve the efficiency of metaproteomics for hydrothermal vent microbiota, we firstly constructed a microbial gene database (HVentDB) based on 117 public metagenomic samples from hydrothermal vents and proposed a metaproteomic analysis strategy, which takes the advantages of not only the sample-matched metagenome, but also the metagenomic information released publicly in the community of hydrothermal vents. A two-stage false discovery rate method was followed up to control the risk of false positive. By applying our community-supported strategy to a hydrothermal vent sediment sample, about twice as many peptides were identified when compared with the ways against the sample-matched metagenome or the public reference database. In addition, more enriched and explainable taxonomic and functional profiles were detected by the HVentDB-based approach exclusively, as well as many important proteins involved in methane, amino acid, sugar, glycan metabolism and DNA repair, etc. The new metaproteomic analysis strategy will enhance our understanding of microbiota, including their lifestyles and metabolic capabilities in extreme environments. The database HVentDB is freely accessible from http://lilab.life.sjtu.edu.cn:8080/HventDB/main.html.

M6A2Target: a comprehensive database for targets of m6A writers, erasers and readers

2020 ◽  
Author(s):  
Shuang Deng ◽  
Hongwan Zhang ◽  
Kaiyu Zhu ◽  
Xingyang Li ◽  
Ying Ye ◽  
...  
Keyword(s):  
High Throughput ◽  
Target Gene ◽  
Target Genes ◽  
Biological Processes ◽  
Public Repository ◽  
Reversible Process ◽  
Comprehensive Database ◽  
Dynamic Modification ◽  
Gene Database ◽  
User Friendly

Abstract N6-methyladenosine (m6A) is the most abundant posttranscriptional modification in mammalian mRNA molecules and has a crucial function in the regulation of many fundamental biological processes. The m6A modification is a dynamic and reversible process regulated by a series of writers, erasers and readers (WERs). Different WERs might have different functions, and even the same WER might function differently in different conditions, which are mostly due to different downstream genes being targeted by the WERs. Therefore, identification of the targets of WERs is particularly important for elucidating this dynamic modification. However, there is still no public repository to host the known targets of WERs. Therefore, we developed the m6A WER target gene database (m6A2Target) to provide a comprehensive resource of the targets of m6A WERs. M6A2Target provides a user-friendly interface to present WER targets in two different modules: ‘Validated Targets’, referred to as WER targets identified from low-throughput studies, and ‘Potential Targets’, including WER targets analyzed from high-throughput studies. Compared to other existing m6A-associated databases, m6A2Target is the first specific resource for m6A WER target genes. M6A2Target is freely accessible at http://m6a2target.canceromics.org.

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