Causal relationship inference for a large-scale cellular network
نویسندگان
چکیده
منابع مشابه
Causal relationship inference for a large-scale cellular network
MOTIVATION Cellular networks usually consist of numerous chemical species, such as DNA, RNA, proteins and small molecules, etc. Different biological tasks are generally performed by complex interactions of these species. As these interactions can rarely be directly measured, it is widely recognized that causal relationship identification is essential in understanding biological behaviors of a c...
متن کاملLarge scale inference and tomography for network monitoring and diagnosis
Today's Internet is a massive, distributed network which continues to explode in size as ecommerce and related activities grow. The heterogeneous and largely unregulated structure of the Internet renders tasks such as dynamic routing, optimized service provision, service level veri cation, and detection of anamolous/malicious behavior increasingly challenging tasks. The problem is compounded by...
متن کاملCausal inference with large‐scale assessments in education from a Bayesian perspective: a review and synthesis
Background With the reauthorization of the United States Elementary and Secondary Education Act (referred to in 2001 as No Child Left Behind–NCLB), attention focused on the need for evidenced-based education research, particularly education policies and interventions that rest on what NCLB referred to as “scientifically based research.” In practice, this focus on scientifically based education ...
متن کاملLarge-Scale Inference of Network-Service Disruption upon Natural Disasters
Large-scale natural disasters cause external disturbances to networking infrastructure that lead to large-scale network-service disruption. To understand the impact of natural disasters to networks, it is important to localize and analyze network-service disruption after natural disasters occur. This work studies an inference of network-service disruption caused by the real natural disaster, Hu...
متن کاملBagging Statistical Network Inference from Large-Scale Gene Expression Data
Modern biology and medicine aim at hunting molecular and cellular causes of biological functions and diseases. Gene regulatory networks (GRN) inferred from gene expression data are considered an important aid for this research by providing a map of molecular interactions. Hence, GRNs have the potential enabling and enhancing basic as well as applied research in the life sciences. In this paper,...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Bioinformatics
سال: 2010
ISSN: 1460-2059,1367-4803
DOI: 10.1093/bioinformatics/btq325