Genix Bioinformatics

omics intelligence for precise medicine

Unlimitted cloud space, state-of-the-art tools, poweful reports

Human genome is the most spectacular epic in nature

Composed of 6.4 Billion words (base pairs), stuctured into 23 chapters (Chromosone pairs).

We can read and decode our geomes like poetry and provide zen level insights

tools to carryout state-of-the analysis
to perform complex studies
large and diverse sequence collection
Case reports
for personalized medical

The genix powerhouse

We can read and decode our geomes like poetry and provide zen level insights

Build, run and share pipelines with zero setup time from anywhere

Battle tested, state-of-the-art pipelines from pioneers of Bioinformatics around the world.

Data and computing resources always always

Now you can dare to dream big without waiting for humangous investment in sequencing machines and datacenters.

Largest cohorts of sequencing data

Unlimitted cloud storage to assist your next ground breaking discovery

Biomarker discovery

The basic objective of biomarker search is to identify factors that indicate the presence of a particular disease or an abnormal condition. The identification of molecular biomarkers from a multitude of test compounds and components is equivalent of the feature subset selection problem (FSS) known in the field of machine learning.

Power of deep learning in ligand-based drug discovery

Two kinds of problem should be solved in order to make the models built using deep neural networks, especially generative models, a valuable option in ligand-based drug discovery

Baskin II. Epub 2020 Mar 31

De novo drug design with AI

De novo design, the generation of novel molecular entities with desired pharmacological properties from scratch, can be considered as one of the most challenging computer-assisted tasks in drug discovery, due to the cardinality of the chemical space of drug-like molecules.

Automated synthesis planning

The majority of all known organic compounds can be synthesized with a limited number of robust reactions. However, reliable and fully automated synthesis planning in chemistry is a challenge that is yet to be met.

No black box computing

Explainable AI, multitask, and meta-learning will pave the way for a new generation of predictive models with increased interpretability and robust performance in low-data regimes.

Data based lead discovery

From Conventional to Machine Learning Methods

Artificial intelligence, including ma-chine learning, is an emerging field that has positively impacted the drug discovery process. Deep reinforcement learning is a subdivision of machine learning that combines artificial neural networks with reinforcement-learning architectures.

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