SLIMS Version 6.2 has been Released
Genohm, an Agilent company, has released the latest version of SLIMS, our flagship Laboratory Information Management System (LIMS) + Electronic Laboratory Notebook (ELN) solution.
We strive to meet the demanding needs of the ambitious domain of lab technology. SLIMS is constantly improved to provide the best end user experience, integrated environments, and customized functionality possible.
SLIMS 6.2 comes with new features and space-saving visual adjustments
Extra Context for Data Collection
New License Models
De-Cluttered User Menu
Further Improvements in this Version
- The style of checkboxes has been changed to switches.
- Notification Setup moved into new Scheduled Jobs module.
- New Groovy can trigger recalculations in related fields.
- Grid widgets centralized in the Grid Templates module, and Vaadin Flows can be used in Dashboards.
- Content Statuses can be created, modified, and deleted in the Statuses module.
- NovaSeq is supported in Workflows with similar integration to HiSeq.
- Output and Unused Input samples can be transferred to the next Protocol step.
- Version panel has been moved into a dropdown to take up less space.
- Custom Fields can be used on the enroll content form.
- Dynamic Filter Expressions can be used on the Product default field.
- A Sort action was added for use with Grid Templates.
NIH Clinical Center Releases Data Trove of 32,000 CT ImagesNews
The National Institutes of Health’s Clinical Center has made a large-scale dataset of CT images publicly available to help the scientific community improve detection accuracy of lesions. While most publicly available medical image datasets have less than a thousand lesions, this dataset, named DeepLesion, has over 32,000.
Analytical Tool Predicts Disease-Causing GenesNews
Predicting genes that can cause disease due to the production of truncated or altered proteins that take on a new or different function, rather than those that lose their function, is now possible thanks to an international team of researchers that has developed a new analytical tool to effectively and efficiently predict such candidate genes.
Researchers Move Closer to Completely Optical Artificial Neural NetworkNews
Researchers have shown that it is possible to train artificial neural networks directly on an optical chip. The significant breakthrough demonstrates that an optical circuit can perform a critical function of an electronics-based artificial neural network and could lead to less expensive, faster and more energy efficient ways to perform complex tasks such as speech or image recognition.