Skip To Main Content
Shihori Tanabe on Muck Rack

Shihori Tanabe

As seen in: Nature, Frontiers, MDPI, Future Medicine
Is this you? As a journalist, you can create a free Muck Rack account to customize your profile, list your contact preferences, and upload a portfolio of your best work. Claim your profile

Get in touch with Shihori

Contact Shihori, search articles and posts on X, monitor coverage, and track replies from one place.

Learn more about Muck Rack

Actions

Share this page

Is this you?

As a journalist, you can create a free Muck Rack account to customize your profile, list your contact preferences, and upload a portfolio of your best work.
Claim your profile

Articles

Accelerating AOP Development in the AOP-Wiki with AI: A Practical Road Map for the Community Click to copy article link Article link copied!

|
By VIKAS KUMAR, Shihori Tanabe, Daniel L. Villeneuve
| dx.doi.org
Bottlenecks in AOP Development Click to copy section linkSection link copied! Over the past 15 years, the adverse outcome pathway (AOP) framework has become a foundational element of next-generation risk assessment (NGRA), providing a structured, mechanistic representation of toxicological causality, from molecular initiating events (MIE), through key events (KE), to adverse outcomes (AO) of regulatory relevance.
Open in Who Shared Issue with article?

Pan-cancer analysis of RNA expression signatures associated with cancer tissue architecture - British Journal of Cancer

|
By Katsushige Kawase, Hiroyoshi Y. Tanaka, Shihori Tanabe
| Nature Verified
Abstract Tissue architecture of cancer deviates from that of normal tissue and is closely linked to various features of cancer, including invasion and tumor immunity. However, pan-cancer analyses of cancer tissue architecture (CTA) remain limited. We applied non-negative matrix factorization to the expression data of 593 CTA-related genes from 28 cancer types in the Cancer Genome Atlas Project dataset, identifying seven distinct CTA signatures.
Open in Who Shared Issue with article?

Artificial Intelligence Approach in Machine Learning-Based Modeling and Networking of the Coronavirus Pathogenesis Pathway

|
By Shihori Tanabe, Sabina Quader, Ryuichi Ono, Hiroyoshi Y. Tanaka
| Preprints.org
Choose an area of interest and we will send you notifications of new preprints at your preferred frequency.
Open in Who Shared View Duplicates (698) Issue with article?
See all 14 articles