The second annual Big Data Conference and Workshop hosted by CCS encouraged business leaders, including UM alumni, to dive into big data. For years, global companies like Airbnb, MasterCard, and Fitbit have used “big data” to better understand the dynamic landscape of business and consumer engagement. In South Florida, the trending topic of big data […]More Information
Brought to you by CCS, CTSI, and the Graduate School, this 2-day workshop will provide you with the basic computing skills and best practices needed to be productive in a small research team.More Information
Join us on Saturday, January 20th, as CCS hosts a hands-on Meetup Group workshop on extracting information from scientific publication metadata.More Information
This workshop is designed to provide a foundation of basic concepts that all programming depends on, using R as an example.More Information
This annual symposium brings together experts in systems biology, data science, drug discovery and translational medicine from academia, industry and government to present their latest research and exchange new ideas and approaches in data driven biomedical research.More Information
The CCS Members who are interested in Social Systems Informatics (led by Program Director Daniel Messinger) have launched a Speaker Series. As the first guest, the group is pleased to present a trio of events around Brian Uzzi. The main event, a TALK on 2/14 entitled “A Simple Model of the Shift from Low to High […]More Information
This conference gathers leaders in academia, professional practice, and industry to examine the Smart Cities phenomenon in relation to emerging trends and technology. This year’s topics TBA soon . . .More Information
Digital Mapping of Informal Cities is a collaborative effort of UM architects, computer software engineers, and geographers to document communities that are literally off the map—and thus lacking essential services—with drone-based aerial photography and computational methods.More Information
This paper describes a collection of signal processing methods and a toolbox for extracting and analyzing vibrato-related parameters from solo audio recordings.
Poster "Ensemble Modeling Approach Targeting Heterogeneous RNA-Seq data: Application to Melanoma Pseudogenes" was presented at the Big Data in Biomedicine Conference at Stanford University.
This report reviews highlights from a two-day meeting involving the BD2K CFPWG to provide insights on trends and considerations in advancing Big Data science for biomedical research in the United States.
With the rise of digital biomarkers, its role in precision medicine has become an important area of interest . . .
In what sense is a city smart? There are established entities defining this rich area of cross-disciplinary studies, and they refer to social, technical, economic, and . . .
The results of our analysis show that by the time infants reach 4 months of age both mothers and infants time their smiles in a purposeful, goal-oriented manner . . .
Cancer: The role of 'non-coding' genes Transcriptomic profiling of head and neck tumors suggests a prominent role for non-protein-coding genes in carcinogenesis.
CCS Postdoctoral Researcher Mohamed Sordo has launched Musikipedia.org, a powerful web application for analyzing and streaming music. Musikipedia stands at the forefront of music analysis . . .
BRAF protein kinase is a crucial player in melanoma, as it belongs to the highly oncogenic RAS/RAF/MEK/ERK signaling pathway . . .
This project focuses on improving housing opportunities for residents of low- to moderate-income Miami neighborhoods . . .
This paper studies a subclass of finite dynamical systems the synchronous BFDS where the states are Boolean and the state update takes place in discrete time and at the same on all objects.
Extracted relations are evaluated intrinsically by assessing their linguistic quality, as well as extrinsically by assessing the extent to which they map an existing music knowledge base.
Library data are often hard to analyze because these data come from unconnected sources, and the data sets can be very large.