☆ Thanks to Andrew Foster, Dilip Mookherjee, and J research design. Thanks to Linda Bui, Sonia Bhalotra, Rem pants at Brandeis, the IGC-ISI Conference in New Delh Fletcher School for Law and Diplomacy at Tufts Unive NEUDC 2012, ISI Economic Growth and Development C 2013, PAA 2013, IGC-ISI South Asia Growth Conference 20 to Rema Hanna and Michael Greenstone for sharing th Control Board's (CPCB) ...

In this thesis, GEMS (a Generic Environment for Multiprocessor Simulations) is presented. GEMS is a simulation environment written in the Superlog language, which simulates a configurable shared-memory multiprocessor system. Simulation focuses on the memory hierarchy and the system interconnect. Part of GEMS is a directory-based cache coherence protocol. This protocol is an adaptation of the bu...

The teacher's guide, Microscopic Explorations: A GEMS Festival Guide (Brady and Willard, 1998), is the result of a partnership between Great Explorations in Math and Science (GEMS), a program of the Lawrence Hall of Science (LHS), the public science and curriculum development center of the University of California, Berkeley, and the Microscopy Society of America (MSA). Microscopic Exploration s...

The advent of microarray technology has revolutionized the search for genes that are differentially expressed across a range of cell types or experimental conditions. Traditional clustering methods, such as hierarchical clustering, are often difficult to deploy effectively since genes rarely exhibit similar expression pattern across a wide range of conditions. Biclustering of gene expression da...

The success of treatment of patients with cancer depends on establishing an accurate diagnosis. To this end, we have built a system called GEMS (gene expression model selector) for the automated development and evaluation of high-quality cancer diagnostic models and biomarker discovery from microarray gene expression data. In order to determine and equip the system with the best performing diag...

Graph embedding, which constructs vector representation of nodes in a network, has shown effectiveness many graph analysis tasks, such as node classification, clustering, and link prediction. However, due to the complexity embedding models (GEMs) their nontransparency hyperparameters, evaluation comparison results retaining original features, consequently, selection suitable GEMs according task...

Genome-scale metabolic models (GEMs) have proven useful as scaffolds for the integration of omics data for understanding the genotype-phenotype relationship in a mechanistic manner. Here, we evaluated the presence/absence of proteins encoded by 15,841 genes in 27 hepatocellular carcinoma (HCC) patients using immunohistochemistry. We used this information to reconstruct personalized GEMs for six...