基于语义路径覆盖的Gene Ontology术语间语义相似性度量方法

进行GO(gene ontology)语义相似性度量是解决生物学数据集成中语义异构问题的重要方法。传统方法主要是基于距离的度量和基于信息量的度量。文中提出了一种基于语义路径覆盖的度量方法,并实现了其中Combine算法。该算法首先计算出每个节点的信息量,然后分别计算两个节点的语义路径的交的节点信息量之和以及这两个节点语义路径的并的节点信息量之和,将这两者之间的比率作为相似性度量值。实验结果表明该算法具有较高的相关系数。

Gene Ontology在生物数据整合中的应用

异构数据的高效整合,在生物数据呈爆炸性增长、生物数据库复杂度不断增加的今天,具有重要的理论价值和实际意义。该文基于BioDW——一个整合的生物信息学数据仓库平台,利用统一的GeneOntology语义模型,建立异构数据库之间的语义链接,在概念和联系层次上有效地解决了生物异构数据的整合问题,实现了对生物数据智能化的多重、复合和交叉检索,为生物信息的进一步研究奠定了坚实的基础。

GoPipe:批量序列的Gene Ontology注释和统计分析(英文)

随着后基因组时代的到来,批量的测序,特别是EST的测序,逐渐成为普通实验室的日常工作. 这些新的序列往往需要进行批量的Gene Ontology (GO)的注释及随后的统计分析. 但是目前除了Goblet以外,并没有软件适合对未知序列进行批量的GO注释,而GoBlet因为具有上载量的限制,以及仅仅利用BLAST作为预测工具,所以仍有许多不足之处. 开发了一个软件包GoPipe,通过整合BLAST和InterProScan的结果来进行序列注释,并提供了进一步作统计比较的工具. 主程序接收任意个BLAST和InterProScan的结果文件,并依次进行文本分析、数据整合、去除冗余、统计分析和显示等工作. 还提供了统计的工具来比较不同输入对GO的分布来挖掘生物学意义. 另外,在交集工作模式下,程序取InterProScan和BLAST结果的交集,在测试数据集中,其精确度达到99.1%,这大大超过了InterProScan本身对GO预测的精确度,而敏感度只是稍微下降. 较高的精确度、较快的速度和较大的灵活性使它成为对未知序列进行批量Gene Ontology注释的理想的工具. 上述软件包可以在网站(http://gopipe.fishgenome.org/ ) 免费获得或者与作者联系获取.

一种基于Gene Ontology注释信息的基因选择算法

基因选择算法是辅助生物学分析最重要的方法之一,但这类统计学算法受样本量相对基因数目过少的困扰。提出一种结合Gene Ontology(GO)注释信息的基因选择算法,用GO注释接近基因的方差的加权平均进行修正,增强小样本量下对总体的估计,进而寻找差异表达基因。将该算法与其他5种常见算法对比,以选择出的基因为特征构建分类器,以分类器的可靠性作为衡量算法的标准。3组芯片实验的结果表明,该算法在小样本情况下具有一定优势。亦有Pubmed文献证明,该算法可以鉴别出其他算法未曾发现的致病基因。该方法所建立起来的框架,是把生物学注释信息引入算法改进的一种有效尝试。

采用基于Gene Ontology的聚类方法研究白血病的遗传异质性

采用基因表达谱可以研究基因功能模块与疾病异质性之间的关系。根据两套白血病基因表达谱数据,将富集高变异基因的Gene Ontology基因功能模块作为特征功能模块,将疾病样本聚为两类。通过对比原始多类标签,采用聚类评估指标来分析两类化聚类结果的效果,并探讨特征功能模块与疾病异质性之间的关系。实验结果显示:在两套不同的白血病基因表达谱数据中得到的特征功能模块类似,它们对白血病亚型有较强的分型能力。

pLoc-mGpos: Incorporate Key Gene Ontology Information into General PseAAC for Predicting Subcellular Localization of Gram-Positive Bacterial Proteins

The basic unit in life is cell.?It contains many protein molecules located at its different organelles. The growth and reproduction of a cell as well as most of its other biological functions are performed via these proteins. But proteins in different organelles or subcellular locations have different functions. Facing?the avalanche of protein sequences generated in the postgenomic age, we are challenged to develop high throughput tools for identifying the subcellular localization of proteins based on their sequence information alone. Although considerable efforts have been made in this regard, the problem is far apart from being solved yet. Most existing methods can be used to deal with single-location proteins only. Actually, proteins with multi-locations may have some special biological functions that are particularly important for drug targets. Using the ML-GKR (Multi-Label Gaussian Kernel Regression) method,?we developed a new predictor called “pLoc-mGpos” by in-depth extracting the key information from GO (Gene Ontology) into the Chou’s general PseAAC (Pseudo Amino Acid Composition)?for predicting the subcellular localization of Gram-positive bacterial proteins with both single and multiple location sites. Rigorous cross-validation on a same stringent benchmark dataset indicated that the proposed pLoc-mGpos predictor is remarkably superior to “iLoc-Gpos”, the state-of-the-art predictor for the same purpose.?To maximize the convenience of most experimental scientists, a user-friendly web-server for the new powerful predictor has been established at http://www.jci-bioinfo.cn/pLoc-mGpos/, by which users can easily get their desired results without the need to go through the complicated mathematics involved.

RNA sequencing of exosomes secreted by fibroblast and Schwann cells elucidates mechanisms underlying peripheral nerve regeneration

Exosomes exhibit complex biological functions and mediate a variety of biological processes,such as promoting axonal regeneration and functional recove ry after injury.Long non-coding RNAs(IncRNAs)have been reported to play a crucial role in axonal regeneration.Howeve r,the role of the IncRNA-microRNAmessenger RNA(mRNA)-competitive endogenous RNA(ceRNA)network in exosome-mediated axonal regeneration remains unclear.In this study,we performed RNA transcriptome sequencing analysis to assess mRNA expression patterns in exosomes produced by cultured fibroblasts(FC-EXOs)and Schwann cells(SCEXOs).Diffe rential gene expression analysis,Gene Ontology analysis,Kyoto Encyclopedia of Genes and Genomes analysis,and protein-protein intera ction network analysis were used to explo re the functions and related pathways of RNAs isolated from FC-EXOs and SC-EXOs.We found that the ribosome-related central gene Rps5 was enriched in FC-EXOs and SC-EXOs,which suggests that it may promote axonal regeneration.In addition,using the miRWalk and Starbase prediction databases,we constructed a regulatory network of ceRNAs targeting Rps5,including 27 microRNAs and five IncRNAs.The ceRNA regulatory network,which included Ftx and Miat,revealed that exsosome-derived Rps5 inhibits scar formation and promotes axonal regeneration and functional recovery after nerve injury.Our findings suggest that exosomes derived from fibro blast and Schwann cells could be used to treat injuries of peripheral nervous system.

SNOMED CT: A Clinical Terminology but Also a Formal Ontology

Context and Objective: Over the past few decades, terminologies developed for clinical descriptions have been increasingly used as key resources for knowledge management, data integration, and decision support to the extent that today they have become essential in the biomedical and health field. Among these clinical terminologies, some may possess the characteristics of one or several types of representation. This is the case for the Systematized Nomenclature of Human and Veterinary Medicine—Clinical Terms (SNOMED CT), which is both a clinical medical terminology and a formal ontology based on the principles of semantic web. Methods: We present and discuss, on one hand, the compliance of SNOMED CT with the requirements of a reference clinical terminology and, on the other hand, the specifications of the features and constructions of descriptive of SNOMED CT. Results: We demonstrate the consistency of the reference clinical terminology SNOMED CT with the principles stated in James J. Cimino’s desiderata and we also show that SNOMED CT contains an ontology based on the EL profile of OWL2 with some simplifications. Conclusions: The duality of SNOMED CT shown is crucial for understanding the versatility, depth, and scope in the health field.

A review of the literature on the use of CRISPR/Cas9 gene therapy to treat hepatocellular carcinoma

Noncoding RNAs instruct the Cas9 nuclease to site speifillyl cleave DNA in the CRISPR/Cas9 system.Despite the high incidence of hepatocellular carcinoma(HCC),the patient's outcome is poor.As a result of the emergence of therapeutic resistance in HCC patients,dlinicians have faced difficulties in treating such tumor.In addition,CRISPR/Cas9 screens were used to identify genes that improve the dlinical response of HCC patients.It is the objective of this article to summarize the current understanding of the use of the CRISPR/Cas9 system for the treatment of cancer,with a particular emphasis on HCC as part of the current state of knowledge.Thus,in order to locate recent developments in oncology research,we examined both the Scopus database and the PubMed database.The ability to selectively interfere with gene expression in combinatorial CRISPR/Cas9 screening can lead to the discovery of new effective HCC treatment regimens by combining clinically approved drugs.Drug resistance can be overcome with the help of the CRISPR/Cas9 system.HCC signature genes and resistance to treatment have been uncovered by genome-scale CRISPR activation screening although this method is not without limitations.It has been extensively examined whether CRISPR can be used as a tool for disease research and gene therapy.CRISPR and its applications to tumor research,particularly in HCC,are examined in this study through a review of the literature.

Comparative Ontology of Theories of Space and Time

With a few exceptions, physics theories are based in a conception of time and space;our two major theories, general relativity, and quantum field theory, differ in their conceptions. Key issues herein include mathematics, logic, intuition, experiment, and ontology, with emphasis on simultaneity and dimensionality of the world. The treatment is through ontological comparison of two theories, space-time theory (special relativity) and energy-time theory (local absolute space and universal time). These two theories share many of the same equations but have different ontology.

Ontology-Based News Linking for Semantic Temporal Queries

Daily newspapers publish a tremendous amount of information disseminated through the Internet.Freely available and easily accessible large online repositories are not indexed and are in an un-processable format.The major hindrance in developing and evaluating existing/new monolingual text in an image is that it is not linked and indexed.There is no method to reuse the online news images because of the unavailability of standardized benchmark corpora,especially for South Asian languages.The corpus is a vital resource for developing and evaluating text in an image to reuse local news systems in general and specifically for the Urdu language.Lack of indexing,primarily semantic indexing of the daily news items,makes news items impracticable for any querying.Moreover,the most straightforward search facility does not support these unindexed news resources.Our study addresses this gap by associating and marking the newspaper images with one of the widely spoken but under-resourced languages,i.e.,Urdu.The present work proposed a method to build a benchmark corpus of news in image form by introducing a web crawler.The corpus is then semantically linked and annotated with daily news items.Two techniques are proposed for image annotation,free annotation and fixed cross examination annotation.The second technique got higher accuracy.Build news ontology in protégéusing OntologyWeb Language(OWL)language and indexed the annotations under it.The application is also built and linked with protégéso that the readers and journalists have an interface to query the news items directly.Similarly,news items linked together will provide complete coverage and bring together different opinions at a single location for readers to do the analysis themselves.

Wilm′s tumor gene1肽疫苗Galinpepimut-S在肿瘤免疫治疗中的应用

目的为Wilm′s tumor gene1(WT1)肽疫苗Galinpepimut-S(GPS)用于肿瘤免疫治疗的后续研究提供参考。方法采用计算机检索中国知网、PubMed等数据库自建库起至2022年12月的肿瘤免疫治疗相关文献,总结GPS在肿瘤免疫治疗中的应用现状。结果GPS能激发自身免疫系统,对WT1抗原产生强烈免疫反应而发挥抗肿瘤作用,在卵巢癌、恶性胸膜间皮瘤、急性髓系白血病、多发性骨髓瘤的治疗中均显示出较好的疗效。结论以GPS为代表的肿瘤疫苗是未来肿瘤治疗的重要方向,需进一步进行临床研究,以获取更多数据。

The Ontology of Velocity

Special relativity formulates a world partitioned into frames in relative motion;absolute motion is prohibited by axiom: no preferred frame, with consequences for the ontology of velocity. The best guide to physical reality is experiment, so ontology of velocity is investigated in the context of primordial field theory in terms of three experiments: Michelson-Morley, Michelson-Gale and Hafele-Keating experiments.

Ontology of Relativistic Mass

The term “relativistic mass” defined by equation m=γm0 with γ=(1-v2/c2)-1/2 has a somewhat controversial history, based on special relativity theory, mathematics, logic, intuition, experiment, and ontology. Key is the ontological framework, specifically whether the framework does or does not include gravity. This paper examines both cases, with detailed analysis of gravitomagnetism and of relativistic mass in collisions.

Ontology-Based Crime News Semantic Retrieval System

Every day,the media reports tons of crimes that are considered by a large number of users and accumulate on a regular basis.Crime news exists on the Internet in unstructured formats such as books,websites,documents,and journals.From such homogeneous data,it is very challenging to extract relevant information which is a time-consuming and critical task for the public and law enforcement agencies.Keyword-based Information Retrieval(IR)systems rely on statistics to retrieve results,making it difficult to obtain relevant results.They are unable to understandthe user’s query and thus facewordmismatchesdue to context changes andthe inevitable semanticsof a given word.Therefore,such datasets need to be organized in a structured configuration,with the goal of efficiently manipulating the data while respecting the semantics of the data.An ontological semantic IR systemis needed that can find the right investigative information and find important clues to solve criminal cases.The semantic system retrieves information in view of the similarity of the semantics among indexed data and user queries.In this paper,we develop anontology-based semantic IRsystemthat leverages the latest semantic technologies including resource description framework(RDF),semantic protocol and RDF query language(SPARQL),semantic web rule language(SWRL),and web ontology language(OWL).We have conducted two experiments.In the first experiment,we implemented a keyword-based textual IR systemusing Apache Lucene.In the second experiment,we implemented a semantic systemthat uses ontology to store the data and retrieve precise results with high accuracy using SPARQL queries.The keyword-based system has filtered results with 51%accuracy,while the semantic system has filtered results with 95%accuracy,leading to significant improvements in the field and opening up new horizons for researchers.

Ontology-Driven Analytic Models for Pension Management and Decision Support System

Ontology-Driven Analytic Models for Pension Management are sophisticated approaches that integrate the principles of ontology and analytics to optimize the management and decision-making processes within pension systems. While Ontology-Driven Analytic Models offer significant benefits for pension management, there are also challenges associated with implementing and utilizing the models. Developing a comprehensive and accurate ontology for pension management requires a deep understanding of the domain, including regulatory frameworks, investment strategies, retirement planning, and integration of data from heterogenous sources. Integrating these data into a cohesive ontology can be challenging. This research work leverages on semantic ontology as an approach for structured representation of knowledge about concepts and their relationships, and applies it to analyze and optimize decision support for pension management. The proposed ontology presents a formal and explicit specification of concepts (classes), their attributes, and the relationships between them and provides a shared and standardized understanding of the domain;enabling precise communication and knowledge representation for decision-support. The ontology deploys computational frameworks and analytic models to assess and evaluate data, generate insights, predict future pension fund performance as well as assess risk exposure. The research adopts the Reasoner, SPARQL query and OWL Visualizer executed over Java IDE for modelling the ontology-driven analytics. The approach encapsulated and integrated semantic ontologies with analytical models to enhance the accuracy, contextuality, and comprehensiveness of analyses and decisions within pension systems.

AMME chromosomal region gene 1基因变异矮小相关综合征一例及文献复习

目的探讨1例身材矮小、面中部发育不全患儿的病因,以提高临床医师对特殊矮小综合征的认识。方法收集1例身材矮小、面中部发育不全患儿的临床资料,对患儿及父母行基因检测,并给予患儿常规治疗、随访。结果结合患儿特殊面容及基因检测,诊断为AMMECR1基因变异矮小相关综合征,结合文献复习总结AMMECR1基因变异矮小相关综合征特点。结论AMMECR1基因变异矮小相关综合征是一种罕见的X连锁遗传性疾病,临床主要表现为身材矮小、运动语言落后、肌张力减低、听力损失、面中部发育不全,部分存在心脏改变、腭裂、骨骼改变及椭圆形红细胞增多症、智力落后和肾钙质沉着症。该文报道1例AMMECR1基因新变异引起身材矮小、面中部发育不全患儿的病例资料,结合特殊面容及基因检测,诊断为AMMECR1基因变异矮小相关综合征。AMMECR1基因变异矮小相关综合征是一种罕见的X连锁遗传性疾病,本文初步概括其特点,并结合文献进行分析,以提高临床医师对AMMECR1基因变异矮小相关综合征的诊治。

An Ontology-Based Question Answering System for University Admissions Advising

Question-Answer systems are now very popular and crucial to support human in automatically responding frequent questions in manyfields.However,these systems depend on learning methods and training data.Therefore,it is necessary to prepare such a good dataset,but it is not an easy job.An ontol-ogy-based domain knowledge base is able to help to reason semantic information and make effective answers given user questions.This study proposes a novel chatbot model involving ontology to generate efficient responses automatically.A case study of admissions advising at the International University–VNU HCMC is taken into account in the proposed chatbot.A domain ontology is designed and built based on the domain knowledge of university admissions using Protégé.The Web user interface of the proposed chatbot system is developed as a prototype using NetBeans.It includes a search engine reasoning the ontology and generat-ing answers to users’questions.Two experiments are carried out to test how the system reacts to different questions.Thefirst experiment examines questions made from some templates,and the second one examines normal questions taken from frequent questions.Experimental results have shown that the ontology-based chatbot can release meaningful and long answers.The results are analysed to prove the proposed chatbot is usable and promising.

An Ontology Based Multilayer Perceptron for Object Detection

In object detection,spatial knowledge assisted systems are effective.Object detection is a main and challenging issue to analyze object-related information.Several existing object detection techniques were developed to consider the object detection problem as a classification problem to perform feature selection and classification.But these techniques still face,less computational efficiency and high time consumption.This paper resolves the above limitations using the Fuzzy Tversky index Ontology-based Multi-Layer Perception method which improves the accuracy of object detection with minimum time.The proposed method uses a multilayer forfinding the similarity score.A fuzzy membership function is used to validate the score for predicting the burned and non-burned zone.Experimental assessment is performed with different factors such as classification rate,time complexity,error rate,space complexity,and precision by using the forestfire dataset.The results show that this novel technique can help to improve the classification rate and reduce the time and space complexity as well as error rate than the conventional methods.

Genetic and epigenetic targets of natural dietary compounds as anti-Alzheimer's agents

Alzheimer’s disease is a progressive neurodegenerative disorder and the most common cause of dementia that principally affects older adults.Pathogenic factors,such as oxidative stress,an increase in acetylcholinesterase activity,mitochondrial dysfunction,genotoxicity,and neuroinflammation are present in this syndrome,which leads to neurodegeneration.Neurodegenerative pathologies such as Alzheimer’s disease are considered late-onset diseases caused by the complex combination of genetic,epigenetic,and environmental factors.There are two main types of Alzheimer’s disease,known as familial Alzheimer’s disease(onset<65 years)and late-onset or sporadic Alzheimer’s disease(onset≥65 years).Patients with familial Alzheimer’s disease inherit the disease due to rare mutations on the amyloid precursor protein(APP),presenilin 1 and 2(PSEN1 and PSEN2)genes in an autosomaldominantly fashion with closely 100%penetrance.In contrast,a different picture seems to emerge for sporadic Alzheimer’s disease,which exhibits numerous non-Mendelian anomalies suggesting an epigenetic component in its etiology.Importantly,the fundamental pathophysiological mechanisms driving Alzheimer’s disease are interfaced with epigenetic dysregulation.However,the dynamic nature of epigenetics seems to open up new avenues and hope in regenerative neurogenesis to improve brain repair in Alzheimer’s disease or following injury or stroke in humans.In recent years,there has been an increase in interest in using natural products for the treatment of neurodegenerative illnesses such as Alzheimer’s disease.Through epigenetic mechanisms,such as DNA methylation,non-coding RNAs,histone modification,and chromatin conformation regulation,natural compounds appear to exert neuroprotective effects.While we do not purport to cover every in this work,we do attempt to illustrate how various phytochemical compounds regulate the epigenetic effects of a few Alzheimer’s disease-related genes.