To ensure undisrupted business, large Internet companies need to closely monitor various KPIs (e.g., Page Views, number of online users, and number of orders) of its Web applications, to accurately detect anomalies and trigger timely troubleshooting/mitigation. However, anomaly detection for these seasonal KPIs with various patterns and data quality has been a great challenge, especially without labels. In this paper, we proposed Donut, an unsupervised anomaly detection algorithm based on VAE. Thanks to a few of our key techniques, Donut greatly outperforms a state-of-arts supervised ensemble approach and a baseline VAE approach, and its best F-scores range from 0.75 to 0.9 for the studied KPIs from a top global Internet company. We come up with a novel KDE interpretation of reconstruction for Donut, making it the first VAE-based anomaly detection algorithm with solid theoretical explanation.

Traditional forward genetic screens are limited in the identification of homologous genes with overlapping functions. Here, we report the analyses and assembly of genome-wide protein family definitions that comprise the largest estimate for the potentially redundant gene space in Arabidopsis thaliana. On this basis, a computational design of genome-wide family-specific artificial microRNAs (amiRNAs) was performed using high-performance computing resources. The amiRNA designs are searchable online (http://phantomdb.ucsd.edu). A computationally derived library of 22,000 amiRNAs was synthesized in 10 sublibraries of 1505 to 4082 amiRNAs, each targeting defined functional protein classes. For example, 2964 amiRNAs target annotated DNA and RNA binding protein families and 1777 target transporter proteins, and another sublibrary targets proteins of unknown function. To evaluate the potential of an amiRNA-based screen, we tested 122 amiRNAs targeting transcription factor, protein kinase, and protein phosphatase families. Several amiRNA lines showed morphological phenotypes, either comparable to known phenotypes of single and double/triple mutants or caused by overexpression of microRNAs. Moreover, novel morphological and abscisic acid-insensitive seed germination mutants were identified for amiRNAs targeting zinc finger homeodomain transcription factors and mitogen-activated protein kinase kinase kinases, respectively. These resources provide an approach for genome-wide genetic screens of the functionally redundant gene space in Arabidopsis.

No abstract