Post-Hoc Tests in Statistical Analysis
In this article, we review the function of post-hoc tests in statistical analysis, how to interpret them and when to use them (and not use them).
Looking Beyond the Known – Off- and On-Target Characterization of CRISPR/Cas9 Gene Editing with SWATH DIA
CRISPR/Cas9, a ground-breaking tool for altering genes with the potential to fully cure genetic diseases, has made its way into the clinic, accelerating research on new therapies using this technology.
Time To Say Goodbye to the Traditional BMI?
Scientists from the Institute for Systems Biology (ISB) have created a biological BMI, an alternative to the "traditional" approach. Technology Networks interviewed the lead researchers to understand why it could be a useful alternative measure of health.
ChatGPT for Proteins Predicts Structure
A new artificial intelligence tool can predict the functions of enzymes based on their amino acid sequences, even when the enzymes are unstudied or poorly understood.
Machine Learning Model Ranks Alzheimer's Risks
Using data from nearly half a million individuals, a machine learning model has been used to rank risk factors in order of how strong their association is with the eventual development of Alzheimer’s disease.
Machine Learning Model Could Help Predict Storms
A machine learning system has been developed that can predict storms and hazardous weather four to eight days in advance, enabling the public to prepare.
Embracing Data-Driven Modeling Approaches Into Biopharmaceutical Processing
This article explores new workflows using data-driven modeling to improve culture medium and new control algorithms allowing for better modulation within the bioprocess design space.
Key Techniques in Structural Biology, Their Strengths and Limitations
Structural biology uses a variety of techniques to determine the 3D structures of biomolecules such as proteins, nucleic acids and their complexes. In this article, we consider the key techniques, their role in structural biology, strengths and limitations.
The Wilcoxon Signed-Rank Test
The Wilcoxon signed rank test, which is also known as the Wilcoxon signed rank sum test and the Wilcoxon matched pairs test, is a non-parametric statistical test used to compare two dependent samples (in other words, two groups consisting of data points that are matched or paired). In this article, we explain how and when this test should be used.
Understanding Structural Biology, Its Applications and Creating a Molecular Model
In this article, we consider what structural biology tells us and the techniques used to investigate it, the role of computation and how techniques can be used together to answer questions in a range of application areas.
The Kruskal–Wallis Test
The Kruskal–Wallis test is a statistical test used to compare two or more groups for a continuous or discrete variable. It is a non-parametric test, meaning that it assumes no particular distribution of your data and is analogous to the one-way analysis of variance (ANOVA). The Kruskal–Wallis test is sometimes referred to as the one-way ANOVA on ranks, or the Kruskal–Wallis one-way ANOVA.
How To Guide
How To Future-Proof Your LIMS: Handling Software Updates
Download this guide to explore types of LIMS upgrades, on-premises installation and SaaS installation.
How To Guide
Biosample Management and Data Tracking: Setting Your LIMS Workflow Right
Download this guide to explore important aspects of the LIMS workflow, biosample management and data management.
Ten Guidelines for Adopting Ontologies To Create FAIRer Scientific Data
Deciding to implement ontologies into your data management practices can be daunting and a difficult sell to business stakeholders. This article outlines the challenges and offers 10 guidelines for kickstarting your ontologies journey.
Standardizing Analytical Data With AnIML
This listicle presents AnIML — an open XML-based, vendor-neutral and human-readable file format that can be used to store data from different analytical instruments. This facilitates the achievement of FAIR (i.e., findable, accessible, interoperable and reusable) data which is a prerequisite for proper data management, data stewardship and a successful digital transformation strategy.