The Saccharomyces Genome Database (SGD) stores and organizes information about the nearly 6200 genes in the yeast genome. The information is organized around the 'locus page' and directs users to the detailed information they seek. SGD is endeavoring to integrate the existing information about yeast genes with the large volume of data generated by functional analyses that are beginning to appea...

We establish a data-dependent notion of algorithmic stability for Stochastic Gradient Descent (SGD) and employ it to develop novel generalization bounds. This is in contrast to previous distribution-free algorithmic stability results for SGD which depend on the worstcase constants. By virtue of the data-dependent argument, our bounds provide new insights into learning with SGD on convex and non...

Along the continental margins, rivers and submarine groundwater supply nutrients, trace elements, and radionuclides to the coastal ocean, supporting coastal ecosystems and, increasingly, causing harmful algal blooms and eutrophication. While the global magnitude of gauged riverine water discharge is well known, the magnitude of submarine groundwater discharge (SGD) is poorly constrained. Using ...

The first completed eukaryotic genome sequence was that of the yeast Saccharomyces cerevisiae, and the Saccharomyces Genome Database (SGD; http://www.yeastgenome.org/) is the original model organism database. SGD remains the authoritative community resource for the S. cerevisiae reference genome sequence and its annotation, and continues to provide comprehensive biological information correlate...

The discovery and development of natural products with potent antioxidant, anti-inflammatory, and antiapoptotic properties have been one of the most interesting and promising approaches in the search for the treatment of many neurodegenerative diseases including ischemic stroke. Serum/glucose deprivation (SGD) has served as an excellent in vitro model for the understanding of the molecular mech...

Neutrophil-specific granule deficiency (SGD) is a rare congenital disorder marked by recurrent bacterial infections. Neutrophils from SGD patients lack secondary and tertiary granules and their content proteins and lack normal neutrophil functions. Gene-inactivating mutations in the C/EBPepsilon gene have been identified in 2 SGD patients. Our studies on a third SGD patient revealed a heterozyg...

Asynchronous distributed stochastic gradient descent methods have trouble converging because of stale gradients. A gradient update sent to a parameter server by a client is stale if the parameters used to calculate that gradient have since been updated on the server. Approaches have been proposed to circumvent this problem that quantify staleness in terms of the number of elapsed updates. In th...

We optimize groundwater management in the presence of marine consequences of submarine groundwater discharge (SGD). Concern for marine biota increases the optimal steady-state head level of the aquifer. The model is discussed in general terms for any coastal groundwater resource where SGD has a positive impact on valuable near-shore resources. Our application focuses of the Kona Coast of Hawai’...

The Saccharomyces Genome Database (SGD; http://www.yeastgenome.org/) collects and organizes biological information about the chromosomal features and gene products of the budding yeast Saccharomyces cerevisiae. Although published data from traditional experimental methods are the primary sources of evidence supporting Gene Ontology (GO) annotations for a gene product, high-throughput experiment...

Logistic regression is a technique to map the input feature to the posterior probability for a binary class. The optimal parameter of regression function is obtained by maximizing log likelihood of training data. In this report, we implement two optimization techniques 1) stochastic gradient decent (SGD); 2) limited-memory BroydenFletcherGoldfarbShanno (L-BFGS) to optimize the log likelihood fu...