Close Menu

This week, IBM Research and the KwaZulu-Natal Research Institute for Tuberculosis and HIV (K-RITH) said that they have signed a collaborative agreement to use computational tools developed by IBM to research new and improved treatment options for tuberculosis.

The partners are using IBM's analytics applications to analyze bacterial sequences and data from drug susceptibility tests to better understand the genomic mechanisms that lead to antibiotic resistance and to find new and more effective medicines and diagnostic approaches for the disease.

Get the full story with
GenomeWeb Premium

Only $95 for the
first 90 days*

GenomeWeb Premium gives you:
✔ Full site access
✔ Interest-based email alerts
✔ Access to archives

Never miss another important industry story.

Try GenomeWeb Premium now.

You may already have institutional access!

Check if I qualify.

Already a GenomeWeb or 360Dx Premium member?
Login Now.

*Before your trial expires, we’ll put together a custom quote with your long-term premium options.

Not ready for premium?

Register for Free Content
You can still register for access to our free content.

Researchers in France have explored the genetic history of the blue cheese mold, Forbes reports.

The South China Morning Post reports eight genetic testing firms in Hong Kong are under scrutiny for potentially misleading consumers.

In Science this week: platform to diagnose genetic disease in children, lung disease-causing genetic mutation corrected in mice, and more.

Wired reports on how genetic genealogy's use in forensics has exploded in the year since an arrest in the Golden State Killer case was made.

May
07
Sponsored by
Agilent

This webinar will discuss the implementation of an enterprise-wide clinical genomics platform that is shared across 10 hospitals and research organizations in the Australian State of Victoria.

Jun
17
Sponsored by
Illumina

This webinar will provide an overview of polygenic risk scores, which aggregate dozens of genetic variants that have been linked to disease risk in genome-wide association studies (GWAS) into a single score.