Broschat相关文献与解析，生知库 | 链接生命科学的每一步

Health Care Providers Can Deliver Personalized Precision Diabetes Care and Adopt GRI If It is Incorporated into a Centralized Platform

如果将 GRI 整合到集中式平台中，医疗保健提供者就能提供个性化的精准糖尿病护理并采用 GRI。

期刊:Journal of diabetes science and technology

影响因子:3.7

doi:10.1177/19322968241257005

Oiknine, Ralph; Broschat, Kay; Weir, Maria; Von Rump, Stephen

Sequence determinants of human-cell entry identified in ACE2-independent bat sarbecoviruses: A combined laboratory and computational network science approach

利用实验室和计算网络科学相结合的方法，鉴定出ACE2非依赖性蝙蝠沙贝病毒中人类细胞入侵的序列决定因素。

期刊:EBioMedicine

影响因子:10.8

doi:10.1016/j.ebiom.2022.103990

Khaledian, Ehdieh; Ulusan, Sinem; Erickson, Jeffery; Fawcett, Stephen; Letko, Michael C; Broschat, Shira L

PASS: Protein Annotation Surveillance Site for Protein Annotation Using Homologous Clusters, NLP, and Sequence Similarity Networks

PASS：蛋白质注释监控网站，用于使用同源簇、自然语言处理和序列相似性网络进行蛋白质注释

期刊:Frontiers in Bioinformatics

影响因子:3.9

doi:10.3389/fbinf.2021.749008

Tao, Jin; Brayton, Kelly A; Broschat, Shira L

发表日期：2021

文献求助收藏

A Systematic Approach to Bacterial Phylogeny Using Order Level Sampling and Identification of HGT Using Network Science

利用目级抽样进行细菌系统发育分析及利用网络科学鉴定水平基因转移

期刊:Microorganisms

影响因子:4.2

doi:10.3390/microorganisms8020312

Khaledian, Ehdieh; Brayton, Kelly A; Broschat, Shira L

Whole Proteome Clustering of 2,307 Proteobacterial Genomes Reveals Conserved Proteins and Significant Annotation Issues

对2307个变形菌基因组进行全蛋白质组聚类分析，揭示了保守蛋白和重要的注释问题

期刊:Frontiers in Microbiology

影响因子:4.5

doi:10.3389/fmicb.2019.00383

Lockwood, Svetlana; Brayton, Kelly A; Daily, Jeff A; Broschat, Shira L

发表日期：2019

文献求助收藏

Prediction of T4SS Effector Proteins for Anaplasma phagocytophilum Using OPT4e, A New Software Tool

利用新型软件工具 OPT4e 预测嗜吞噬细胞无形体 T4SS 效应蛋白

期刊:Frontiers in Microbiology

影响因子:4.5

doi:10.3389/fmicb.2019.01391

Esna Ashari, Zhila; Brayton, Kelly A; Broschat, Shira L

细胞生物学

发表日期：2019

文献求助收藏

Using an optimal set of features with a machine learning-based approach to predict effector proteins for Legionella pneumophila

利用基于机器学习的方法，结合最优特征集来预测嗜肺军团菌的效应蛋白

期刊:PLoS One

影响因子:2.6

doi:10.1371/journal.pone.0202312

Esna Ashari, Zhila; Brayton, Kelly A; Broschat, Shira L

发表日期：2019

文献求助收藏

Alignment-free clustering of large data sets of unannotated protein conserved regions using minhashing

利用最小哈希算法对未注释蛋白质保守区域的大型数据集进行无比对聚类

期刊:BMC Bioinformatics

影响因子:3.3

doi:10.1186/s12859-018-2080-y

Abnousi, Armen; Broschat, Shira L; Kalyanaraman, Ananth

发表日期：2018

文献求助收藏

An optimal set of features for predicting type IV secretion system effector proteins for a subset of species based on a multi-level feature selection approach

基于多级特征选择方法，针对部分物种，提出了一组预测IV型分泌系统效应蛋白的最佳特征。

期刊:PLoS One

影响因子:2.6

doi:10.1371/journal.pone.0197041

Esna Ashari, Zhila; Dasgupta, Nairanjana; Brayton, Kelly A; Broschat, Shira L

发表日期：2018

文献求助收藏

Editorial: Machine learning approaches to antimicrobials: discovery and resistance

社论：机器学习在抗菌药物发现与耐药性研究中的应用

Health Care Providers Can Deliver Personalized Precision Diabetes Care and Adopt GRI If It is Incorporated into a Centralized Platform

如果将 GRI 整合到集中式平台中，医疗保健提供者就能提供个性化的精准糖尿病护理并采用 GRI。

Sequence determinants of human-cell entry identified in ACE2-independent bat sarbecoviruses: A combined laboratory and computational network science approach

利用实验室和计算网络科学相结合的方法，鉴定出ACE2非依赖性蝙蝠沙贝病毒中人类细胞入侵的序列决定因素。

PASS: Protein Annotation Surveillance Site for Protein Annotation Using Homologous Clusters, NLP, and Sequence Similarity Networks

PASS：蛋白质注释监控网站，用于使用同源簇、自然语言处理和序列相似性网络进行蛋白质注释

A Systematic Approach to Bacterial Phylogeny Using Order Level Sampling and Identification of HGT Using Network Science

利用目级抽样进行细菌系统发育分析及利用网络科学鉴定水平基因转移

Whole Proteome Clustering of 2,307 Proteobacterial Genomes Reveals Conserved Proteins and Significant Annotation Issues

对2307个变形菌基因组进行全蛋白质组聚类分析，揭示了保守蛋白和重要的注释问题

Prediction of T4SS Effector Proteins for Anaplasma phagocytophilum Using OPT4e, A New Software Tool

利用新型软件工具 OPT4e 预测嗜吞噬细胞无形体 T4SS 效应蛋白

Using an optimal set of features with a machine learning-based approach to predict effector proteins for Legionella pneumophila

利用基于机器学习的方法，结合最优特征集来预测嗜肺军团菌的效应蛋白

Alignment-free clustering of large data sets of unannotated protein conserved regions using minhashing

利用最小哈希算法对未注释蛋白质保守区域的大型数据集进行无比对聚类

An optimal set of features for predicting type IV secretion system effector proteins for a subset of species based on a multi-level feature selection approach

基于多级特征选择方法，针对部分物种，提出了一组预测IV型分泌系统效应蛋白的最佳特征。