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Sybil accounts are fake identities created to unfairly increase the power or resources of a single user. Researchers have long known about the existence of Sybil accounts in online communities such as file-sharing systems, but have not been able to perform large scale measurements to detect them or measure their activities. In this paper, we describe our(More)
N(6)-methyladenosine (m(6)A) is the most prevalent and reversible internal modification in mammalian messenger and noncoding RNAs. We report here that human methyltransferase-like 14 (METTL14) catalyzes m(6)A RNA methylation. Together with METTL3, the only previously known m(6)A methyltransferase, these two proteins form a stable heterodimer core complex of(More)
N(6)-methyladenosine (m(6)A) is the most prevalent internal (non-cap) modification present in the messenger RNA of all higher eukaryotes. Although essential to cell viability and development, the exact role of m(6)A modification remains to be determined. The recent discovery of two m(6)A demethylases in mammalian cells highlighted the importance of m(6)A in(More)
Popular online social networks (OSNs) like Facebook and Twitter are changing the way users communicate and interact with the Internet. A deep understanding of user interactions in OSNs can provide important insights into questions of human social behavior and into the design of social platforms and applications. However, recent studies have shown that a(More)
Fake identities and Sybil accounts are pervasive in today’s online communities. They are responsible for a growing number of threats, including fake product reviews, malware and spam on social networks, and astroturf political campaigns. Unfortunately, studies show that existing tools such as CAPTCHAs and graph-based Sybil detectors have not proven to be(More)
We design novel, asymptotically more efficient data structures and algorithms for programs whose data access patterns exhibit some degree of predictability. To this end, we propose two novel techniques, a <i>pointer</i>-based technique and a <i>locality</i>-based technique. We show that these two techniques are powerful building blocks in making data(More)
As popular tools for spreading spam andmalware, Sybils (or fake accounts) pose a serious threat to online communities such as Online Social Networks (OSNs). Today, sophisticated attackers are creating realistic Sybils that effectively befriend legitimate users, rendering most automated Sybil detection techniques ineffective. In this paper, we explore the(More)
Face recognition is confronted with situations in which face images are captured in various modalities, such as the visual modality, the near infrared modality, and the sketch modality. This is known as heterogeneous face recognition. To solve this problem, we propose a new method called discriminative spectral regression (DSR). The DSR maps heterogeneous(More)
As the popularity of the social media increases, as evidenced in Twitter, Facebook and China’s Renren, spamming activities also picked up in numbers and variety. On social network sites, spammers often disguise themselves by creating fake accounts and hijacking normal users’ accounts for personal gains. Different from the spammers in traditional systems(More)
The ability to construct synthetic gene networks enables experimental investigations of deliberately simplified systems that can be compared to qualitative and quantitative models. If simple, well-characterized modules can be coupled together into more complex networks with behaviour that can be predicted from that of the individual components, we may begin(More)