Sequential anomaly detection in the presence of noise and limited feedback

This paper describes a methodology for detecting anomalies from sequentially observed and potentially noisy data. The proposed approach consists of two main elements: 1) filtering, or assigning a belief or likelihood to each successive measurement based upon our ability to predict it from previous noisy observations and 2) hedging, or flagging potential anomalies by comparing the current belief against a time-varying and data-adaptive threshold. The threshold is adjusted based on the available feedback from an end user. Our algorithms, which combine universal prediction with recent work on online convex programming, do not require computing posterior distributions given all current observations and involve simple primal-dual parameter updates. At the heart of the proposed approach lie exponential-family models which can be used in a wide variety of contexts and applications, and which yield methods that achieve sublinear per-round regret against both static and slowly varying product distributions with marginals drawn from the same exponential family. Moreover, the regret against static distributions coincides with the minimax value of the corresponding online strongly convex game. We also prove bounds on the number of mistakes made during the hedging step relative to the best offline choice of the threshold with access to all estimated beliefs and feedback signals. We validate the theory on synthetic data drawn from a time-varying distribution over binary vectors of high dimensionality, as well as on the Enron email dataset. © 1963-2012 IEEE.

A miR-34a-Numb Feedforward Loop Triggered by Inflammation Regulates Asymmetric Stem Cell Division in Intestine and Colon Cancer.

Emerging evidence suggests that microRNAs can initiate asymmetric division, but whether microRNA and protein cell fate determinants coordinate with each other remains unclear. Here, we show that miR-34a directly suppresses Numb in early-stage colon cancer stem cells (CCSCs), forming an incoherent feedforward loop (IFFL) targeting Notch to separate stem and non-stem cell fates robustly. Perturbation of the IFFL leads to a new intermediate cell population with plastic and ambiguous identity. Lgr5+ mouse intestinal/colon stem cells (ISCs) predominantly undergo symmetric division but turn on asymmetric division to curb the number of ISCs when proinflammatory response causes excessive proliferation. Deletion of miR-34a inhibits asymmetric division and exacerbates Lgr5+ ISC proliferation under such stress. Collectively, our data indicate that microRNA and protein cell fate determinants coordinate to enhance robustness of cell fate decision, and they provide a safeguard mechanism against stem cell proliferation induced by inflammation or oncogenic mutation.