Current and future directions in network biology

no code implementations • 15 Sep 2023 • Marinka Zitnik, Michelle M. Li, Aydin Wells, Kimberly Glass, Deisy Morselli Gysi, Arjun Krishnan, T. M. Murali, Predrag Radivojac, Sushmita Roy, Anaïs Baudot, Serdar Bozdag, Danny Z. Chen, Lenore Cowen, Kapil Devkota, Anthony Gitter, Sara Gosline, Pengfei Gu, Pietro H. Guzzi, Heng Huang, Meng Jiang, Ziynet Nesibe Kesimoglu, Mehmet Koyuturk, Jian Ma, Alexander R. Pico, Nataša Pržulj, Teresa M. Przytycka, Benjamin J. Raphael, Anna Ritz, Roded Sharan, Yang shen, Mona Singh, Donna K. Slonim, Hanghang Tong, Xinan Holly Yang, Byung-Jun Yoon, Haiyuan Yu, Tijana Milenković

As such, it is expected to help shape short- and long-term vision for future computational and algorithmic research in network biology.

Data Integration

Graphery: Interactive Tutorials for Biological Network Algorithms

no code implementations • 6 Feb 2021 • Heyuan Zeng, Jinbiao Zhang, Gabriel A. Preising, Tobias Rubel, Pramesh Singh, Anna Ritz

Graphery is a hands-on tutorial webserver designed to help biological researchers understand the fundamental concepts behind commonly-used graph algorithms.

Navigate

Improved Differentially Private Analysis of Variance

no code implementations • 1 Mar 2019 • Marika Swanberg, Ira Globus-Harris, Iris Griffith, Anna Ritz, Adam Groce, Andrew Bray

Hypothesis testing is one of the most common types of data analysis and forms the backbone of scientific research in many disciplines.

Two-sample testing