M Hadi Amini,Ahmed Imteaj,Panos M Pardalos
M Hadi Amini
Traditionally, networks have been studied in an independent fashion. With the emergence of novel smart city technologies, coupling among networks has been strengthened. To capture the ever-increasing coupling, we explain the notion of inter...
Valerie McCutcheon,George Bray
Valerie McCutcheon
Is the proliferation of work-based games just a distraction, or can they actually help us to acquire work-specific knowledge? This Opinion explains why we can see the benefits of such games, despite initial skepticism. Players learn from li...
Jon Crowcroft
Jon Crowcroft
The stages of digital technology readiness are viewed through the lens of three contemporary and widely discussed examples, namely distributed ledger technology, machine learning, and the internet of things. I use these examples to clarify ...
KG-COVID-19: A Framework to Produce Customized Knowledge Graphs for COVID-19 Response [0.03%]
KG-COVID-19：用于冠状病毒肺炎响应的定制知识图谱框架
Justin T Reese,Deepak Unni,Tiffany J Callahan et al.
Justin T Reese et al.
Integrated, up-to-date data about SARS-CoV-2 and COVID-19 is crucial for the ongoing response to the COVID-19 pandemic by the biomedical research community. While rich biological knowledge exists for SARS-CoV-2 and related viruses (SARS-CoV...
Using Machine Learning to Identify Adverse Drug Effects Posing Increased Risk to Women [0.03%]
利用机器学习识别对女性风险增加的药物不良反应
Payal Chandak,Nicholas P Tatonetti
Payal Chandak
Adverse drug reactions are the fourth leading cause of death in the US. Although women take longer to metabolize medications and experience twice the risk of developing adverse reactions compared with men, these sex differences are not comp...
Argonaut: A Web Platform for Collaborative Multi-omic Data Visualization and Exploration [0.03%]
.Argoaurt：一个协作的多组学数据可视化和探索网络平台
Dain R Brademan,Ian J Miller,Nicholas W Kwiecien et al.
Dain R Brademan et al.
Researchers now generate large multi-omic datasets using increasingly mature mass spectrometry techniques at an astounding pace, facing new challenges of "Big Data" dissemination, visualization, and exploration. Conveniently, web-based data...
Statistical Hypothesis Testing versus Machine Learning Binary Classification: Distinctions and Guidelines [0.03%]
统计假设检验与机器学习二元分类的区别和指南
Jingyi Jessica Li,Xin Tong
Jingyi Jessica Li
Making binary decisions is a common data analytical task in scientific research and industrial applications. In data sciences, there are two related but distinct strategies: hypothesis testing and binary classification. In practice, how to ...
High Tech, High Risk: Tech Ethics Lessons for the COVID-19 Pandemic Response [0.03%]
高技术，高风险：针对COVID-19大流行应对的技术伦理课程
Emanuel Moss,Jacob Metcalf
Emanuel Moss
The COVID-19 pandemic has, in a matter of a few short months, drastically reshaped society around the world. Because of the growing perception of machine learning as a technology capable of addressing large problems at scale, machine learni...
Yuanfang Guan,Xueqing Wang,Hongyang Li et al.
Yuanfang Guan et al.
One in eight women develops invasive breast cancer in her lifetime. The frontline protection against this disease is mammography. While computer-assisted diagnosis algorithms have made great progress in generating reliable global prediction...
Cell-Type-Specific Proteogenomic Signal Diffusion for Integrating Multi-Omics Data Predicts Novel Schizophrenia Risk Genes [0.03%]
用于整合多组学数据预测新型精神分裂症风险基因的细胞类型特异性蛋白质基因组信号扩散
Abolfazl Doostparast Torshizi,Jubao Duan,Kai Wang
Abolfazl Doostparast Torshizi
Accumulation of diverse types of omics data on schizophrenia (SCZ) requires a systems approach to model the interplay between genome, transcriptome, and proteome. We introduce Markov affinity-based proteogenomic signal diffusion (MAPSD), a ...