检索结果-内蒙古大学图书馆

Concordance between an FDA-approved companion diagnostic and an alternative assay kit for assessing homologous recombination deficiency in ovarian cancer

引用

GYNECOLOGIC ONCOLOGY 2024年 184卷 67-73页

作者： Wehn, Amy K. Qiu, Ping Lunceford, Jared Yarunin, Alexander Cristescu, Razvan Liu, Li Roessler, Kyria Bilke, Sven Timms, Kirsten M. Weichert, Wilko Marton, Matthew J. Merck & Co Inc MRL Rahway NJ 07065 USA Merck & Co Inc Biostat & Res Decis Sci MRL Rahway NJ USA AstraZeneca Affairs Global Oncol Milton Cambridge England Merck & Co Inc Data & Genom Sci Rahway NJ USA Illumina Assay Dev San Diego CA USA Illumina Bioinformatics San Diego CA USA Myriad Genet Inc Salt Lake City UT USA Tech Univ Munich Inst Pathol Munich Germany 126 E Lincoln Ave Rahway NJ 07065 USA

Objective: Authors evaluated the performance of a commercially available next-generation sequencing assay kit;this was based on genomic content from Illumina's TruSight (TM) Oncology 500 research assay that identifies BRCA variants and proprietary algorithms licensed from Myriad and, with additional genomic content, measures the homologous recombination deficiency (HRD) genomic instability score (GIS) in tumor tissue (TSO 500 HRD assay). Methods: data from the TSO 500 HRD assay were compared with data from the Myriad MyChoice (R) CDx PLUS assay (Myriad assay). Prevalence rates for overall HRD status and BRCA mutations (a deleterious or suspected deleterious BRCA1 or BRCA2 mutation or both) and assay agreement rates for HRD GIS and BRCA analysis were assessed in ovarian tumor samples. Pearson correlations of the continuous HRD GIS and analytic sensitivity and specificity were evaluated. Results: The prevalence of overall HRD positivity was 51.2% (TSO 500 HRD assay) versus 49.2% (Myriad assay) and the prevalence of BRCA mutations was 27.6% (TSO 500 HRD assay) versus 25.5% (Myriad assay). After post-processing optimization, concordance of the HRD GIS was 0.980 in all samples and 0.976 in the non-BRCA mutation cohort;the area under the receiver operating characteristic curve was 0.995 and 0.992, respectively. Conclusions: Comparison between the Illumina and Myriad assays showed that overall HRD status, the individual components of BRCA analysis, and HRD GIS detection results were highly concordant (>93%), suggesting the TSO 500 HRD assay will approach the analytical accuracy of the FDA-approved Myriad assay.

关键词： Homologous recombination de ficiency Genomic instability score Ovarian cancer BRCA

来源：评论

学校读者我要写书评

暂无评论

Artificial Intelligence in IBD: How Will It Change Patient Management?

引用

Current Treatment Options in Gastroenterology 2023年第4期21卷 365-377页

作者： Stone, Molly L. Stidham, Ryan W. Division of Gastroenterology Department of Internal Medicine Michigan Medicine Ann Arbor USA Department of Computational Medicine and Bioinformatics University of Michigan Ann Arbor USA Michigan Institute for Data Science (MIDAS) University of Michigan Ann Arbor USA

Artificial intelligence (AI) is quickly evolving and will be integral to the management of IBD patients. In this review, we provide an overview of technologies powering applications for Crohn’s disease and ulcerative colitis, with particular attention to information extraction from imaging and text records. Recent data highlight machine learning capability to replicate expert interpretation and judgment at population scale with accuracy in endoscopic and histology disease grading. Computer vision techniques are also detecting important findings difficult for even expert clinicians to reliably appreciate, including dysplasia on colonoscopy and fibrosis on CT and MRI imaging. Further, segmentation and radiomics can extract more information than manually possible, enabling new possibilities for disease measurement. Finally, natural language processing (NLP) is showing promise automatically extracting IBD-related medical concepts from text and generating conversational responses for both clinicians and patients. Quickly mounting evidence supports AI reliability grading disease severity in endoscopy, histology, and imaging. In particular use cases, AI can surpass the ability of humans for disease feature detecting and the generation of new measures of IBD activity. Ultimately, AI-powered information extraction will provide significant incremental improvement in the personalization predictions of outcomes and treatment course in IBD.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Large-scale moral machine experiment on large language models

arXiv

引用

arXiv 2024年

作者： Ahmad, Muhammad Shahrul Zaim bin Takemoto, Kazuhiro Department of Bioscience and Bioinformatics Kyushu Institute of Technology Fukuoka Iizuka Japan Faculty of Engineering and Technology Multimedia University Melaka Malaysia Data Science and AI Research Center Kyushu Institute of Technology Fukuoka Iizuka Japan

The rapid advancement of Large Language Models (LLMs) and their potential integration into autonomous driving systems necessitates understanding their moral decision-making capabilities. While our previous study examined four prominent LLMs using the Moral Machine experimental framework, the dynamic landscape of LLM development demands a more comprehensive analysis. Here, we evaluate moral judgments across 52 different LLMs, including multiple versions of proprietary models (GPT, Claude, Gemini) and open-source alternatives (Llama, Gemma), to assess their alignment with human moral preferences in autonomous driving scenarios. Using a conjoint analysis framework, we evaluated how closely LLM responses aligned with human preferences in ethical dilemmas and examined the effects of model size, updates, and architecture. Results showed that proprietary models and open-source models exceeding 10 billion parameters demonstrated relatively close alignment with human judgments, with a significant negative correlation between model size and distance from human judgments in open-source models. However, model updates did not consistently improve alignment with human preferences, and many LLMs showed excessive emphasis on specific ethical principles. These findings suggest that while increasing model size may naturally lead to more human-like moral judgments, practical implementation in autonomous driving systems requires careful consideration of the trade-off between judgment quality and computational efficiency. Our comprehensive analysis provides crucial insights for the ethical design of autonomous systems and highlights the importance of considering cultural contexts in AI moral decision-making. © 2024, CC BY.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Sequence-Based Predicting Bacterial Essential ncRNAs Algorithm by Machine Learning

引用

Intelligent Automation & Soft Computing 2023年第6期36卷 2731-2741页

作者： Yuan-Nong Ye Ding-Fa Liang Abraham Alemayehu Labena Zhu Zeng Bioinformatics and Biomedical Big data Mining Laboratory Department of Medical InformaticsSchool of Big HealthGuizhou Medical UniversityGuiyang550025China Cells and Antibody Engineering Research Center of Guizhou Province Key Laboratory of Biology and Medical EngineeringSchool of Biology and EngineeringGuizhou Medical UniversityGuiyang550025China Key Laboratory of Environmental Pollution Monitoring and Disease Control Ministry of EducationGuizhou Medical UniversityGuiyang550025China College of Computational and Natural Sciences Dilla UniversityDilla419Ethiopia

Essential ncRNA is a type of ncRNAwhich is indispensable for the sur-vival of *** essential ncRNAs cannot encode proteins,they are as important as essential coding genes in *** have got wide variety of applications such as antimicrobial target discovery,minimal genome construction and evolution *** present,the number of species required for the deter-mination of essential ncRNAs in the whole genome scale is still very few due to the traditional methods are time-consuming,laborious and *** addition,tra-ditional experimental methods are limited by the organisms as less than 1%of bacteria can be cultured in the ***,it is important and necessary to develop theories and methods for the recognition of essential non-coding *** this paper,we present a novel method for predicting essential ncRNA by using both compositional and derivative features calculated by information theory of ncRNA *** method was developed with Support Vector Machine(SVM).The accuracy of the method was evaluated through cross-species cross-vali-dation and found to be between 0.69 and *** shows that the features we selected have good performance for the prediction of essential ncRNA using ***,the method can be applied for discovering essential ncRNAs in bacteria.

关键词： bioinformatics biological information theory biomedical informatics

来源：评论

学校读者我要写书评

暂无评论

Twnbiome: a public database of the healthy Taiwanese gut microbiome

引用

BMC bioinformatics 2023年第1期24卷 1-13页

作者： Chattopadhyay, Amrita Lee, Chien-Yueh Lee, Ya-Chin Liu, Chiang-Lin Chen, Hsin-Kuang Li, Yung-Hua Lai, Liang-Chuan Tsai, Mong-Hsun Ni, Yen-Hsuan Chiu, Han-Mo Lu, Tzu-Pin Chuang, Eric Y. Bioinformatics and Biostatistics Core Centers of Genomic and Precision Medicine National Taiwan University Taipei Taiwan Department of Biomedical Engineering China Medical University Taichung Taiwan Department of Public Health Institute of Health Data Analytics and Statistics National Taiwan University Taipei Taiwan Graduate Institute of Biomedical Electronics and Bioinformatics National Taiwan University Taipei Taiwan Center for Biotechnology National Taiwan University Taipei Taiwan Graduate Institute of Physiology National Taiwan University Taipei Taiwan Institute of Biotechnology National Taiwan University Taipei Taiwan College of Medicine National Taiwan University Taipei Taiwan Department of Internal Medicine National Taiwan University Hospital Taipei Taiwan Institute of Health Data Analytics and Statistics National Taiwan University Taipei Taiwan Biomedical Technology and Device Research Laboratories Industrial Technology Research Institute Hsinchu Taiwan Division Research and Development Center for Medical Devices National Taiwan University Taipei Taiwan

With new advances in next generation sequencing (NGS) technology at reduced costs, research on bacterial genomes in the environment has become affordable. Compared to traditional methods, NGS provides high-throughput sequencing reads and the ability to identify many species in the microbiome that were previously unknown. Numerous bioinformatics tools and algorithms have been developed to conduct such analyses. However, in order to obtain biologically meaningful results, the researcher must select the proper tools and combine them to construct an efficient pipeline. This complex procedure may include tens of tools, each of which require correct parameter settings. Furthermore, an NGS data analysis involves multiple series of command-line tools and requires extensive computational resources, which imposes a high barrier for biologists and clinicians to conduct NGS analysis and even interpret their own data. Therefore, we established a public gut microbiome database, which we call Twnbiome, created using healthy subjects from Taiwan, with the goal of enabling microbiota research for the Taiwanese population. Twnbiome provides users with a baseline gut microbiome panel from a healthy Taiwanese cohort, which can be utilized as a reference for conducting case-control studies for a variety of diseases. It is an interactive, informative, and user-friendly database. Twnbiome additionally offers an analysis pipeline, where users can upload their data and download analyzed results. Twnbiome offers an online database which non-bioinformatics users such as clinicians and doctors can not only utilize to access a control set of data, but also analyze raw data with a few easy clicks. All results are customizable with ready-made plots and easily downloadable tables. database URL: http://***/ . © 2023, The Author(s).

关键词： database systems

来源：评论

学校读者我要写书评

暂无评论

Prediction of Kinase-Substrate Associations Using The Functional Landscape of Kinases and Phosphorylation Sites 28

Prediction of Kinase-Substrate Associations Using The Functi...

引用

28th Pacific Symposium on Biocomputing, PSB 2023

作者： Ayati, Marzieh Yilmaz, Serhan Blasco Tavares Pereira Lopes, Filipa Chance, Mark Koyuturk, Mehmet Department Of Computer Science University Of Texas Rio Grande Valley EdinburgTX United States Department Of Computer And Data Sciences ClevelandOH United States Department Of Nutrition ClevelandOH United States Center For Proteomics And Bioinformatics ClevelandOH United States Case Comprehensive Cancer Center Case Western Reserve University ClevelandOH United States

ISBN: (纸本)9789811270604

Protein phosphorylation is a key post-translational modification that plays a central role in many cellular processes. With recent advances in biotechnology, thousands of phosphorylated sites can be identified and quantified in a given sample, enabling proteome-wide screening of cellular signaling. However, for most (> 90%) of the phosphorylation sites that are identified in these experiments, the kinase(s) that target these sites are unknown. To broadly utilize available structural, functional, evolutionary, and contextual information in predicting kinase-substrate associations (KSAs), we develop a network-based machine learning framework. Our framework integrates a multitude of data sources to characterize the landscape of functional relationships and associations among phosphosites and kinases. To construct a phosphosite-phosphosite association network, we use sequence similarity, shared biological pathways, co-evolution, co-occurrence, and co-phosphorylation of phosphosites across different biological states. To construct a kinase-kinase association network, we integrate protein-protein interactions, shared biological pathways, and membership in common kinase families. We use node embeddings computed from these heterogeneous networks to train machine learning models for predicting kinase-substrate associations. Our systematic computational experiments using the PhosphositePLUS database shows that the resulting algorithm, NetKSA, outperforms two state-of-the-art algorithms, including KinomeXplorer and LinkPhinder, in overall KSA prediction. By stratifying the ranking of kinases, NetKSA also enables annotation of phosphosites that are targeted by relatively less-studied kinases. Availability: The code and data are available at ***/NetKSA/. © 2022 The Authors.

关键词： Association reactions

来源：评论

学校读者我要写书评

暂无评论

Literature Based Discovery (LBD): Towards Hypothesis Generation and Knowledge Discovery in Biomedical Text Mining

arXiv

引用

arXiv 2023年

作者： Bhasuran, Balu Murugesan, Gurusamy Natarajan, Jeyakumar DRDO-BU Center for Life Sciences Bharathiar University Campus TamilNadu Coimbatore India Data mining and Text mining Laboratory Department of Bioinformatics Bharathiar University TamilNadu Coimbatore India

Biomedical knowledge is growing in an astounding pace with a majority of this knowledge is represented as scientific publications. Text mining tools and methods represents automatic approaches for extracting hidden patterns and trends from this semi structured and unstructured data. In Biomedical Text mining, Literature Based Discovery (LBD) is the process of automatically discovering novel associations between medical terms otherwise mentioned in disjoint literature sets. LBD approaches proven to be successfully reducing the discovery time of potential associations that are hidden in the vast amount of scientific literature. The process focuses on creating concept profiles for medical terms such as a disease or symptom and connecting it with a drug and treatment based on the statistical significance of the shared profiles. This knowledge discovery approach introduced in 1989 still remains as a core task in text mining. Currently the ABC principle based two approaches namely open discovery and closed discovery are mostly explored in LBD process. This review starts with general introduction about text mining followed by biomedical text mining and introduces various literature resources such as MEDLINE, UMLS, MESH, and SemMedDB. This is followed by brief introduction of the core ABC principle and its associated two approaches open discovery and closed discovery in LBD process. This review also discusses the deep learning applications in LBD by reviewing the role of transformer models and neural networks based LBD models and its future aspects. Finally, reviews the key biomedical discoveries generated through LBD approaches in biomedicine and conclude with the current limitations and future directions of LBD. © 2023, CC BY.

关键词： data mining

来源：评论

学校读者我要写书评

暂无评论

Implementation of Face Patterns and Smile Recognition for Intelligent Class Attendance Systems 6

Implementation of Face Patterns and Smile Recognition for In...

引用

6th International Conference on Computer and Informatics Engineering, IC2IE 2023

作者： Miftakhurrokhmat Suparyanto, Teddy Elwirehardja, Gregorius Natanael Karimah, Shofiyati Nur Pardamean, Bens Bina Nusantara University Bioinformatics and Data Science Research Center Jakarta Indonesia School of Computer Science Bina Nusantara University Computer Science Department Jakarta Indonesia Universitas Amikom Yogyakarta Faculty of Computer Science Department of Informatics Yogyakarta Indonesia Bina Nusantara University Binus Graduate Program - Master of Computer Science Computer Science Department Jakarta Indonesia

ISBN: (纸本)9798350345162

Students 'attendance in class is one important success parameter in face-to-face learning processes. Conventional attendance systems, such as paper-based attendance sheets or identity card systems, require a long time in the manual recapitulation process. Without additional verifications, even computer vision-based methods are prone to fraudulent practices by the students instead of gaining their excitement and attention in a class. To stimulate students' attention in a class, this work designs an intelligent class attendance system, in which facial pattern and smile recognition are implemented by using the latter as an additional task-based verification to reduce the risks of fake attendance. For the face recognition module, this pilot study used FaceNet as a feature extractor combined with SVM for classification, whereas the Haar cascade algorithm is used for recognizing smiles. This face recognition pipeline was implemented as a service installed on minicomputers or Internet of Things (IoT) devices in each classroom and connected to an IP camera. Every recorded attendance will be sent as a notification to a mobile application for students that requires their active participation to confirm it with a smiling self-photo. The proposed pipeline obtained 92.86% accuracy on the test data, and 66.67% accuracy when evaluated in a real-life simulation setting through the implemented system. The lower accuracy in the simulation indicated that further improvements are indispensable, especially since the model obtained 28.57% False Negative Rate. Future studies will need to acquire more data and experiment with more efficient methods of attendance verification. © 2023 IEEE.

关键词： class attendance convolutional neural network deep learning face recognition smile

来源：评论

学校读者我要写书评

暂无评论

UniSleepPos: Sleep Posture Identification System Utilizing Millimeter-wave Radar

UniSleepPos: Sleep Posture Identification System Utilizing M...

引用

IEEE International Conference on bioinformatics and Biomedicine (BIBM)

作者： Kun Liu Min Li Chu He Xu Tian Junbin Mao Min Zeng Jin Liu Xinjiang Engineering Research Center of Big Data and Intelligent Software School of Software Xinjiang University Urumqi China Hunan Provincial Key Lab on Bioinformatics School of Computer Science and Engineering Central South University Changsha China

ISBN: (数字)9798350386226

ISBN: (纸本)9798350386233

Sleep posture identification is crucial for accurately assessing sleep quality and diagnosing related diseases. In the realm of non-intrusive sleep monitoring, non-contact technologies are becoming increasingly mainstream. Millimeter-wave radar is frequently utilized in sleep posture identification due to its high resolution, strong penetration, and excellent sensitivity. However, traditional radar-based methods for sleep posture identification often struggle with reliability when dealing with diverse individuals and complex sleep environments. To address these challenges, we propose UniSleepPos, which designs a novel dual-view fusion mechanism to integrate depression and elevation angle signals obtained from radar, thus accurately capturing the posture information of the monitored subject in three-dimensional space. Furthermore, we combine sleep posture identification with individual characteristics, utilizing existing individual labels as prior knowledge to assist in sleep posture identification. The integration of prior knowledge provides a valuable information source for the model, helping to enhance its understanding of the data and improve its performance. We collected sleep posture data from eight volunteers using millimeter-wave radar devices under various environmental conditions. Leave-one-subject-out experiments were conducted to validate the effectiveness of UniSleepPos. The results indicated that UniSleepPos significantly outperforms existing methods, demonstrating its potential for practical applications.

关键词： Performance evaluation Sensitivity Spaceborne radar Millimeter wave radar Depression data models Reliability Monitoring Signal resolution Diseases

来源：评论

学校读者我要写书评

暂无评论

A full genome assembly reveals drought stress effects on gene expression and metabolite profiles in blackcurrant(Ribes nigrum L.)

引用

园艺研究（英文） 2025年第2期12卷 188-204页

作者： Freya Maria Rosemarie Ziegler Vivien Rosenthal Jose G.Vallarino Franziska Genzel Sarah Spettmann Łukasz Seliga Sylwia Keller-Przybyłkowicz Lucas Munnes Anita Sønsteby Sonia Osorio Björn Usadel CEPLAS Institute of Bio-and Geosciences(IBG-4:Bioinformatics)& Bioeconomy Science Center(BioSC)Forschungszentrum JülichWilhelm-Johnen-StraßeD-52425 JülichGermany Faculty of Mathematics and Natural Sciences CEPLASInstitute for Biological Data ScienceUniversitätsstr.1D-40225 DüsseldorfGermany Cluster of Excellence on Plant Sciences(CEPLAS) Heinrich Heine University DüsseldorfUniversitätsstr.1D-40225 DüsseldorfGermany Faculty of Mathematics and Natural Sciences CEPLASInstitute for Biological Data ScienceUniversitätsstr.1D-40225 DüsseldorfGermany Cluster of Excellence on Plant Sciences(CEPLAS) Heinrich Heine University DüsseldorfUniversitätsstr.1D-40225 DüsseldorfGermany Departamento de Biología Molecular y Bioquímica Campus de TeatinosInstituto de Hortofruticultura Subtropical y Mediterránea'La Mayora'Universidad de Málaga-Consejo Superior de Investigaciones Científicas29010 MálagaSpain CEPLAS Institute of Bio-and Geosciences(IBG-4:Bioinformatics)& Bioeconomy Science Center(BioSC)Forschungszentrum JülichWilhelm-Johnen-StraßeD-52425 JülichGermany Department of Plant Crop breeding INHORTNational Institute of Horticultural ResearchKonstytucji 3 Maja 1/396-100 SkierniewicePoland Faculty of Mathematics and Natural Sciences CEPLASInstitute for Biological Data ScienceUniversitätsstr.1D-40225 DüsseldorfGermany NIBIO Norwegian Institute of Bioeconomy ResearchDivision of Food Production and Society HorticulturePb.115NO-1431 ÅsNorway

Blackcurrant(Ribes nigrum L.,family Grossulariaceae)is a perennial shrub that is widely cultivated for its edible *** are rich in antioxidants,vitamin C,and anthocyanins,making them a valuable ingredient in the food and beverage ***,prolonged periods of drought during the fruiting season lead to drought stress,which has serious ecological and agricultural implications,inhibiting blackcurrant growth and reducing *** facilitate the analysis of underlying molecular processes,we present the first high-quality chromosome-scale and partially haplotype-resolved assembly of the blackcurrant genome(*** Langtraubige),also the first in the family *** used this genomic reference to analyze the transcriptomic response of blackcurrant leaves and roots to drought stress,revealing differentially expressed genes with diverse functions,including those encoding the transcription factors bZIP,bHLH,MYB,and WRKY,and tyrosine kinase-like kinases such as PERK and *** expression was correlated with the abundance of primary metabolites,revealing 14 with significant differences between stressed leaves and controls indicating a metabolic response to drought *** acids such as proline were more abundant under stress conditions,whereas organic acids were *** genomic and transcriptomic data from this study can be used to develop more robust blackcurrant cultivars that thrive under drought stress conditions.

关键词： expression profiles drought stress nigrum genome full gene assembly blackcurrant

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：