A scientific research platform to drive new knowledge in genetics
The GeneRecommender genomic platform constitute a new free tool for life science researchers to discover new targets, optimize resources for the analysis, and gather new insights about their current research topics.
Functionalities and features
GeneRecommender provides you with suggestions as to which other genes and proteins may relate to your current research. For that purpose, we have developed a Deep Learning Neural Network that is trained on all available scientific literature and is able to predict which targets you might consider.
In spite of the complexity of our artificial intelligence engine, leveraging AI to provide support to your research is easy. You will be asked to insert genes and diseases related to your current research topic, and you will be presented with up to 50 new targets suggested by the AI.
Keeping you in the best possible position for efficiency and effectiveness is important to us because we know the nature of your job is extremely challenging. Therefore, GeneRecommender provides different features to help your scientific research.
Get the most out of the GeneRecommender
Researchers like you may use GeneRecommender for a variety of projects and in many different situations. In spite of the fact that applications can be virtually infinite, developers have identified some areas where it can have a profound impact on your research projects. Indeed, the system was created in order to work by emulating a researcher in the genomic field, automatizing the reasoning process that brings the researcher from a hypothesis to a discovery. Discover more here below.
Have you ever experienced a deadlock while working on an important publication? AI can help you in achieving your objectives faster and more effectively.
The system could be beneficial in this situation because it could provide a new perspective. Unlike humans, machines are not subject to the same biases we have and that might make human work difficult (they have others).
In fact, the algorithm tries to find the best angle (in terms of relationships between other genes) to observe each gene. In this case, a proposal from an AI system can be the solution to a painful stalemate in a research topic with high information content.
A SIMPLE WORKFLOW, ALL IN A FEW STEPS
Register at www.generecommender.com with your institutional email
The platform is designed to be as intuitive as possible, however we have provided a video tutorial that covers all the features developed to make your recommendation tailored to suit your needs!
Price & Sponsorship
We spent years developing the AI system behind GeneRecommender. We decided to give it for free to the academic community since we know how important their job is for modern society. In order to sustain this project, we asked reagent distributors (one per country) to sponsor the platform.
For this reason, within the platform, you will find the name of the company that decided to provide you with this tool for free. Furthermore, together with each recommended gene, you will also be able to access their product catalog through a direct link to their webshop. Thereby we ask that you register with your academic email address. If you are a researcher working for a company or you are willing to use the system for commercial purposes you can contact us HERE.
Academic researchers are able to use GeneRecommender for free for life thanks to our generous sponsors. Therefore, the number of available recommendations may vary depending on your country and preferences. More Details are available HERE.
Tech Fast: AIRA Project
This platform has been developed within the context of the AIRA project, founded by Regione Lombardia, by TheProphetAI. TheProphetAI is a Milan-based start-up that with AIRA aimed to develop an AI-based system to support life science and diagnostic actors in the early stages of product development. The AI system uses advanced machine learning and deep learning techniques to increase efficiency and reduce costs. Thanks to the project, the startup was able to build the current platform and the underlying algorithm called DeepProphet2 which represents a major innovation for researchers in the field.