Aditya Bharadwaj PhD Candidate
Computer Science Department
Virginia Tech

Aditya Bharadwaj

Flud: a hybrid crowd-algorithm approach for visualizing biological networks

Many fields of science require meaningful and visually appealing layouts of graphs. However, the problem remains challenging due to multiple conflicting criteria and complex domain-specific constraints. In this workshop paper, we present a gamified graph layout task where the goal of the players is to create a layout that optimises a score based on user-defined priorities. We propose a novel hybrid approach wherein non-experts and simulated annealing algorithm build on each other’s progress. To facilitate this collaborative process, we have developed Flud, an online game with a purpose that leverages the combination of cognitive abilities of humans to observe patterns, and the computational accuracy of simulated annealing to draw graph layouts that can help scientists visualize and understand complex networks. visualize and understand complex networks.

Critter: Augmenting Creative Work with Dynamic Checklists, Automated Quality Assurance, and Contextual Reviewer Feedback

Checklists and guidelines have played an increasingly important role in complex tasks ranging from the cockpit to the operating theater. Their role in creative tasks like design is less explored. In a needfinding study with expert web designers, we identified designers’ challenges in adhering to a checklist of design guidelines. We built Critter, which addressed these challenges with three components: Dynamic Checklists that progressively disclose guideline complexity with a self-pruning hierarchical view, AutoQA to automate common quality assurance checks, and guideline-specific feedback provided by a reviewer to highlight mistakes as they appear. In an observational study, we found that the more engaged a designer was with Critter, the fewer mistakes they made in following design guidelines. Designers rated the AutoQA and contextual feedback experience highly, and provided feedback on the tradeoffs of the hierarchical Dynamic Checklists. We additionally found that a majority of designers rated the AutoQA experience as excellent and felt that it increased the quality of their work. Finally, we discuss broader implications for supporting complex creative tasks.

GraphSpace: stimulating interdisciplinary collaborations in network biology

Networks have become ubiquitous in systems biology. Visualization is a crucial component in their analysis. However, collaborations within research teams in network biology are hampered by software systems that are either specific to a computational algorithm, create visualizations that are not biologically meaningful, or have limited features for sharing networks and visualizations. We present GraphSpace, a web-based platform that fosters team science by allowing collaborating research groups to easily store, interact with, layout and share networks

Availability and implementation: Anyone can upload and share networks at In addition, the GraphSpace code is available at if a user wants to run his or her own server.

XTalkDB: A Database of Signaling Pathway Crosstalk

Analysis of signaling pathways and their crosstalk is a cornerstone of systems biology. Thousands of papers have been published on these topics. Surprisingly, there is no database that carefully and explicitly documents crosstalk between specific pairs of signaling pathways. We have developed XTALKDB ( to fill this very important gap. XTALKDB contains curated information for 650 pairs of pathways from over 1600 publications. In addition, the database reports the molecular components (e.g. proteins, hormones, microRNAs) that mediate crosstalk between a pair of pathways and the species and tissue in which the crosstalk was observed. The XTALKDB website provides an easy-to-use interface for scientists to browse crosstalk information by querying one or more pathways or molecules of interest.