Learn More
Transcription factors (TFs) and their specific interactions with targets are crucial for specifying gene-expression programs. To gain insights into the transcriptional regulatory networks in embryonic stem (ES) cells, we use chromatin immunoprecipitation coupled with ultra-high-throughput DNA sequencing (ChIP-seq) to map the locations of 13(More)
We present a variety of new architectural features and training procedures that we apply to the generative adversarial networks (GANs) framework. Using our new techniques, we achieve state-of-the-art results in semi-supervised classification on MNIST, CIFAR-10 and SVHN. The generated images are of high quality as confirmed by a visual Turing test: Our model(More)
Oct4 and Nanog are transcription factors required to maintain the pluripotency and self-renewal of embryonic stem (ES) cells. Using the chromatin immunoprecipitation paired-end ditags method, we mapped the binding sites of these factors in the mouse ES cell genome. We identified 1,083 and 3,006 high-confidence binding sites for Oct4 and Nanog, respectively.(More)
This paper describes InfoGAN, an information-theoretic extension to the Gener-ative Adversarial Network that is able to learn disentangled representations in a completely unsupervised manner. InfoGAN is a generative adversarial network that also maximizes the mutual information between a small subset of the latent variables and the observation. We derive a(More)
Real-world relational data are seldom stationary, yet traditional collaborative filtering algorithms generally rely on this assumption. Motivated by our sales prediction problem, we propose a factor-based algorithm that is able to take time into account. By introducing additional factors for time, we formalize this problem as a tensor factorization with a(More)
Recently, researchers have made significant progress combining the advances in deep learning for learning feature representations with reinforcement learning. Some notable examples include training agents to play Atari games based on raw pixel data and to acquire advanced manipulation skills using raw sensory inputs. However , it has been difficult to(More)
Triple-negative breast cancer (TNBC) is a highly diverse group of cancers, and subtyping is necessary to better identify molecular-based therapies. In this study, we analyzed gene expression (GE) profiles from 21 breast cancer data sets and identified 587 TNBC cases. Cluster analysis identified 6 TNBC subtypes displaying unique GE and ontologies, including(More)
We prove that Bimatrix, the problem of finding a Nash equilibrium in a two-player game, is complete for the complexity class <b>PPAD</b> (Polynomial Parity Argument, Directed version) introduced by Papadimitriou in 1991. Our result, building upon the work of Daskalakis et al. [2006a] on the complexity of four-player Nash equilibria, settles a long standing(More)
With increasing presence and adoption of Web services on the World Wide Web, Quality-of-Service (QoS) is becoming important for describing nonfunctional characteristics of Web services. In this paper, we present a collaborative filtering approach for predicting QoS values of Web services and making Web service recommendation by taking advantages of past(More)
Mitochondrial dysfunction is a hallmark of beta-amyloid (Abeta)-induced neuronal toxicity in Alzheimer's disease (AD). Here, we demonstrate that Abeta-binding alcohol dehydrogenase (ABAD) is a direct molecular link from Abeta to mitochondrial toxicity. Abeta interacts with ABAD in the mitochondria of AD patients and transgenic mice. The crystal structure of(More)