We are at a pivotal moment where AI can transform the future of biologics discovery. By optimizing data for AI-driven workflows, your organization can unlock new possibilities in therapeutic development.
Integrating AI into research pipelines can involve many hurdles, depending on the workflows associated with each organization’s specific drug discovery applications.
Effective API solutions facilitate the seamless integration of data from multiple sources, automating processes and enabling advanced data analysis with deep-learning models.
Many therapeutic discovery processes suffer from slow pipelines, inefficient resource distribution, and difficulties in adopting new technologies. One of the main reasons is the lack of workflow customization solutions. In this article, we will discuss the challenges and benefits of implementing tailored workflows and introduce our Last Mile Service.
Reducing barriers for researchers to access highly curated data eliminates repetitive analysis steps and facilitates innovation and progress. We had the honor of delving into this subject with Dr. Felix Breden, Professor Emeritus at Simon Fraser University, and a distinguished member of the AIRR Community.
The main purpose of InSilicoSeq 2.0 is to generate synthetic datasets that imitate real-world scenarios so that scientists and programmers can validate and optimize bioinformatics tools, statistical algorithms, and analytical pipelines.
Precision in clone annotation is vital for sound downstream analysis results. Our immune repertoire processing App, IGX-Profile, was recently benchmarked using a publicly available AIRR dataset with exciting results.
In this interview, we discuss repertoire sequencing – a powerful tool to understand T and B cell response dynamics. We’ll cover repertoire data analysis, promising applications, and the future of this cutting-edge technology.
Our user-centered design approach creates user-friendly software for navigating immune repertoire sequencing data. Learn how it was implemented in the IGX-Track App.
While generation of sequence data has gotten significantly cheaper and easier, annotating immune receptors correctly and in a scalable manner has not. Let’s dive into key challenges of correct receptor identification and quantification and why this fundamental step in the analysis of immune repertoires requires tailor-made methods.
ENPICOM