Deep learning methods used to identify novel genes implicated in tissue regeneration and cancer

January 04, 2018

January 4, 2018, Baltimore, MD: Insilico Medicine, a Baltimore-based next-generation artificial intelligence company specializing in the application of deep learning for drug discovery announced the publication of a new peer-reviewed research paper titled "Use of deep neural network ensembles to identify embryonic-fetal transition markers: repression of COX7A1 in embryonic and cancer cells" in Oncotarget. The paper is a culmination of a collaboration, which started in 2015 with the first applications of deep neural networks (DNNs) to the gene expression data from the highly-controlled and standardized experiments performed by BioTime. Scientists at BioTime started with the cells from several embryonic stem cell lines and differentiated them into the many fully-differentiated cells collecting samples and analyzing the gene expression data during the many stages of differentiation.

"At Biotime and AgeX we aspire to use the most cutting-edge technologies to study aging and regeneration. We contracted Insilico Medicine to develop a deep learning systems for analyzing the differentiation state of the samples before this technology became widely popular. We also developed methods to derive biologically-relevant information from these systems, identified most interesting genes and performed additional experimental validation. It is rare to find genes whose abnormal expression is observed in so many diverse cancer types such as those of the breast, lung, kidney, bone, and muscle," said Michael D. West, Ph.D., CEO of AgeX.

Some of the genes involved in embryonic to fetal transition process displayed a rare profile of being nearly universally dysregulated in diverse types of cancer. One of the most important genes highlighted using the feature importance analysis was COX7A1. The discoveries may lead to novel strategies to induced tissue regeneration as well as treat and diagnose cancer. A short video describing the discovery and AgeX's commercial plans is available for viewing at http://www.agexinc.com.

"We are very happy to be collaborating with AgeX on the applications of AI to regenerative medicine. One of the main challenges with deep learning in biomedicine is experimental validation and the need of expert interpretation which sometimes takes a lot of time. The techniques we used in 2015 could make headlines but with BioTimes highly-diligent scientists we took the time to get the biology right. We hope to use this experience to develop better AI to make humans do more, live longer and feel better", said Alex Zhavoronkov, PhD, CEO of Insilico Medicine, Inc.

Insilico Medicine is scheduled to present its research in the applications of AI to drug discovery and biomarker development at over 30 conferences in 2018. Alex Zhavoronkov will speak and panel at the AI in Pharma Reception organized by another leading AI company, Atomwise and at the WuXi Global Forum 2018 during the JP Morgan Healthcare conference in San Francisco 8-10 of January. During the conference Insilico will also present a live demo of its blockchain- and AI- enabled system for returning the control over the life data back to the individuals called Longenesis.
-end-
Paper Reference:

West M, Labat I, Sternberg H, Larocca D, Nasonkin I, Chapman K, Singh R, Makarev E, Aliper A, Kazennov A, Alekseenko A, Shuvalov N, Cheskidova E, Alekseev A, Artemov A, Putin E, Mamoshina P, Pryanichnikov P, Larocca J, Copeland K, Izumchenko E, Korzinkin M and Zhavoronkov A. Use of deep neural network ensembles to identify embryonic-fetal transition markers: repression of COX7A1 in embryonic and cancer cells, Oncotarget. 2017; in press, https://doi.org/10.18632/oncotarget.23748

About AgeX Therapeutics

AgeX Therapeutics, Inc., a subsidiary of BioTime, Inc. (NYSE American: BTX), is a biotechnology company applying technology relating to cellular immortality and regenerative biology to aging and age-related diseases. The company has three initial areas of product development: pluripotent stem cell-derived brown adipocytes (AGEX-BAT1); vascular progenitors (AGEX-VASC1); and induced Tissue Regeneration (iTR). Initial planned indications for these products are Type 2 diabetes, cardiac ischemia, and tissue regeneration respectively. For more information, please visit http://www.agexinc.com or connect with the company on Twitter or Facebook.

About BioTime

BioTime is a late stage clinical biotechnology company focused on developing and commercializing products addressing degenerative diseases. The Company's current clinical programs are targeting three primary sectors, aesthetics, ophthalmology and cell/drug delivery. Its clinical programs are based on two platform technologies: pluripotent cells, which can become any type of cell in the human body, and cell/drug delivery. Renevia®, a cell delivery product, met its primary endpoint in an EU pivotal trial for the treatment of facial lipoatrophy in HIV patients earlier this year. Submission for approval of Renevia® is expected later this year, with an anticipated commercial launch in 2018. OpRegen®, a retinal pigment epithelium transplant therapy, is in a Phase I/IIa multicenter trial for the treatment of dry age-related macular degeneration, the leading cause of blindness in developing countries. BioTime also has significant equity holdings in two publicly traded companies, Asterias Biotherapeutics, Inc. (NYSE American: AST) and OncoCyte Corporation (NYSE American: OCX), and a private company, AgeX Therapeutics, Inc.

BioTime common stock is traded on the NYSE American and TASE under the symbol BTX. For more information, please visit http://www.biotime.com or connect with the company on Twitter, LinkedIn, Facebook, YouTube, and Google+.

To receive ongoing BioTime corporate communications, please click on the following link to join the Company's email alert list: http://news.biotimeinc.com.

About Insilico Medicine, Inc.

Insilico Medicine, Inc. is a bioinformatics company located at the Emerging Technology Centers in Baltimore with R&D resources in 6 countries. The company is widely recognized by the industry for applying next-generation artificial intelligence technology to drug discovery and aging research. For its pioneering work in the applications of Generative Adversarial Networks (GANs) and Reinforcement Learning (RL) and collaborations with the pharmaceutical companies it was selected as the Top 100 AI companies 2018 by CB Insights and Top 5 AI companies for social impact 2017 by NVIDIA. The company pursues internal drug discovery programs in cancer, dermatological, metabolic and CNS diseases, sarcopenia, fibrosis and senescence. Company website: http://www.insilico.com

For further information, images or interviews, please contact:

Qingsong Zhu, PhD
zhu@pharma.ai

InSilico Medicine, Inc.

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