Graph technology has become a requirement for the modern enterprise. Companies in virtually every industry, from healthcare to energy to financial services, are applying the power of graph analytics ...

The analysis of cancer biology data involves extremely heterogeneous data sets, including information from RNA sequencing, genome-wide copy number, DNA methylation data reporting on epigenetic ...

Thanks to their visual simplicity, bar graphs are popular tools for representing data. But do we really understand how to read them? New research from Wellesley College published in the Journal of ...

The content of courses and the methods by which students learn are crucial in teaching the life sciences (NRC 1999, NRC 2003). Skills in data analysis and graph interpretation are particularly ...

Probabilistic graphs and uncertain data analysis represent a rapidly evolving research domain that seeks to reconcile the inherent imprecision of real-world data with robust computational models. By ...

A new open-source library by Nvidia could be the secret ingredient to advancing analytics and making graph databases faster. The key: parallel processing on Nvidia GPUs. Nvidia has long ago stopped ...

Data Interpretation is an important part of the Quantitative Aptitude section in many competitive exams. It tests the ability to read, understand, and draw conclusions from data presented in the form ...

Design hypotheses about how wetland hydroperiod may affect different groups of species (Knowledge, Comprehension, Application) Produce and analyze graphs comparing permanent and temporary wetlands, ...

Thanks to their visual simplicity, bar graphs are popular tools for representing data. But do we really understand how to read them? New research has found that bar graphs are frequently misunderstood ...