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Published in Michael Hehenberger, Zhi Xia, Huanming Yang, Our Animal Connection, 2020
Michael Hehenberger, Zhi Xia, Huanming Yang
The knowledge accumulated by the global scientific community about model organisms is typically shared in Model Organism Databases (MODs). They are dedicated to the provision of in-depth biological data for intensively studied model organisms. MODs allow researchers to easily find background information on large sets of genes, plan experiments efficiently, combine their data with existing knowledge, and construct novel hypotheses. They allow users to analyze results and interpret datasets. Where possible, MODs share common approaches (such as gene ontology104) to collect and represent biological information. “Gene ontology” is used to describe functions, processes and cellular locations of specific genes. It is a major global initiative to unify the representation of gene and gene product attributes across all species. More specifically, the project aims to (i) maintain and develop its controlled vocabulary; (ii) annotate genes and gene products, and assimilate and disseminate annotation data; (iii) provide tools for easy access to all aspects of the data provided by the project. The scientific community is further sharing software for the curation, visualization, and querying between different MODs. Model Organism Databases are also helpful for projects focused on less well studied species.
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Published in Michael Hehenberger, Zhi Xia, Our Animal Connection, 2019
The knowledge accumulated by the global scientific community about model organisms is typically shared in Model Organism Databases (MODs). They are dedicated to the provision of in-depth biological data for intensively studied model organisms. MODs allow researchers to easily find background information on large sets of genes, plan experiments efficiently, combine their data with existing knowledge, and construct novel hypotheses. They allow users to analyze results and interpret datasets. Where possible, MODs share common approaches (such as gene ontology104) to collect and represent biological information. “Gene ontology” is used to describe functions, processes and cellular locations of specific genes. It is a major global initiative to unify the representation of gene and gene product attributes across all species. More specifically, the project aims to (i) maintain and develop its controlled vocabulary; (ii) annotate genes and gene products, and assimilate and disseminate annotation data; (iii) provide tools for easy access to all aspects of the data provided by the project. The scientific community is further sharing software for the curation, visualization, and querying between different MODs. Model Organism Databases are also helpful for projects focused on less well studied species.
Informatics as a Pathway for Integrating Radiation Oncology into Modern Medicine
Published in Siyong Kim, John Wong, Advanced and Emerging Technologies in Radiation Oncology Physics, 2018
Mark H. Phillips, Wade P. Smith, Kristi R. G. Hendrickson, Alan M. Kalet
Even more explicitly, the Gene Ontology “defines concepts/classes used to describe gene function, and relationships between these concepts. It classifies functions along three aspects: molecular function …, cellular component …, biological process …” whose goal is to “to develop an up-to-date, comprehensive, computational model of biological systems, from the molecular level to larger pathways, cellular and organism-level systems” (GO, 2016).
Novel computer aided diagnostic system using hybrid neural network for early detection of pancreatic cancer
Published in Automatika, 2023
Moschopoulos et al. [10] recommend obtaining the bare minimum of biomarkers for pancreatic cancer diagnosis. To identify tissue samples, the Genetic algorithm (GA) was applied to PDAC data. As a consequence, our algorithm generates a listing of biomarkers that participate the majority essential responsibility in this terrible ailment [10]. Pahari et al. [5] develop spectral clustering algorithms. One of the most dangerous tumours is pancreatic ductal adenocarcinoma [5]. This research looks at the high-dimensional PDAC genetic material appearance dataset from the Gene Expression Omnibus (GEO) database. An innovative Shannon's Entropy-base remoteness measurement used in the direction of distinguishes clusters in the pancreatic dataset. KEGG Pathway analysis is used to identify specific biomarkers. The proposed technique is useful designed for defining biomarkers based on biological understanding and functional similarities of genes as defined by Gene Ontology (GO) terminology.
Hepatic proteomic assessment of oral ingestion of titanium dioxide nano fiber (TDNF) in Sprague Dawley rats
Published in Journal of Environmental Science and Health, Part A, 2022
Worlanyo E. Gato, Ji Wu, Isaac Appiah, Olivia Smith, Haresh Rochani
This paper investigated the hepatic proteomic effects of oral ingestion of titanium dioxide nanofibers. Titanium dioxide nanofibers have been used a variety of applications. Understanding the toxicological implications of these materials is critical for avoiding adverse health effects associated with their use. Analysis of the structure of the materials show that the diameter ranged from 0.18 − 0.29 μm, forming clusters and majority of the fibers were in the rutile phase. To understand toxicity effects, nanofibers were ingested by Sprague Dawley rats. Proteomics assessment revealed more that more than 400 hundred proteins in the liver that may be affected. These proteins are involved in such processes as catalysis of fatty acids by CoA, homocysteine metabolism, beta oxidation and the condensation of carbamoyl phosphate in the urea cycle among others. Further analysis of the protein associations by DAVID bioinformatics tool showed that gene ontology (GO) categories including functional biological process (BP), cellular components (CC) and molecular function (MF). GO categories included 325 biological processes, 140 molecular functions and 70 cellular components appear to be affected from the ingestion of TNDF. Quantitative analysis of specific mRNA transcripts indicated CMBL, GSTM1 and SDS were differentially expressed. In conclusion, it appears that the ingestion of TDNF produced mild toxicological effects in the liver of Sprague Dawley rats.
Norethisterone exposure alters the transcriptome of Marine Medaka (Oryzias melastigma) larvae
Published in Chemistry and Ecology, 2021
Xueyou Li, Xiaona Lin, Yuebi Chen, Zhongduo Wang, Yusong Guo, Gyamfua Afriyie, Ning Zhang, Zhongdian Dong
To determine which genes have transcribed the sequenced fragments, the clean reads were compared to the reference genome (marine medaka genome; NCBI ID 12955). Hisat2 v2.0.5 was used to quickly and accurately compare clean reads with the reference genome, and obtain the location of reads on the reference genome. The new transcripts were assembled by StringTie software v 1.3.3b to obtain predicted genes [23]. Gene ontology (GO) is a comprehensive database describing gene function, which can be divided into three parts: biological processes (BP), cellular components (CC), and molecular functions (MF). Compared with the genomic background, GO functionality in differentially expressed genes (DEGs) was significantly enriched, and the biological functions of significant DEGs were obtained. Taking advantage of the publicly available Kyoto Encyclopedia of Genes and Genomes (KEGG) database, a pathway enrichment analysis was carried out to determine the signal transduction or metabolic pathway with significant enrichment. The cluster Profiler R package was used to perform GO enrichment analysis and KEGG pathway enrichment analysis on DEGs. The threshold value of P < 0.05 was taken as significant for GO functional and KEGG pathway enrichment.