ChaPterS8,9,10and11areConCernedWithdifferentmethodsOfObtainingdata.TheUSeOf SeCondarydataisdiscussedinChaPter8,WhiChintroducestheVarietyOfdatathatareIikeIyto beavailableandSUggeStSWaySinWhiChtheyCanbeused.AdVantageSanddisadvantagesOf SeCondarydataarediscussed,andarangeOftechniquesfbrlocatingthesedata,includingUSing the...
As long-read sequencing technologies continue to advance, the possibility of obtaining maps of DNA and RNA modifications at single-molecule resolution has become a reality. Here we highlight the opportunities and challenges posed by the use of long-read sequencing technologies to study epigenetic and...
Microbiome differential abundance analysis methods for two groups are well-established in the literature. However, many microbiome studies involve more than two groups, sometimes even ordered groups such as stages of a disease, and require different type
On top of that, primary data can be collected quickly and more accurately, allowing you to make evidence-based decisions. In short, primary data offers a betteropportunity to grasp the motivations behind various activitiesthat may seem unrelated but are essential for effective market research and s...
Chris is a managing director in Deloitte’s National Office – Accounting and Reporting Services Group. Chris’ primary areas of expertise are revenue recognition, leasing, accounting for cloud computing...More Get in touch for service offerings ...
even identification and analysis of particular phloem pole cells in Arabidopsis root [34]. However, with primary xylem cells, only differentiating tracheary elements can be analyzed, since mature elements are dead. Similarly in secondary xylem, only undifferentiated and xylem parenchyma cells are alive...
First, we summarize the network environment in which intrusion detection techniques are applied (RQ1), which helps us to analyze the characteristics of the development and application of intrusion detection techniques. Second, we investigate the data preprocessing techniques (RQ2) and intrusion ...
A fused method using a combination of multi-omics data enables a comprehensive study of complex biological processes and highlights the interrelationship of relevant biomolecules and their functions. Driven by high-throughput sequencing technologies, sev
The present study examines the role of feature selection methods in optimizing machine learning algorithms for predicting heart disease. The Cleveland Heart disease dataset with sixteen feature selection techniques in three categories of filter, wrapper,
Our primary learning objective is to infer affinities from raw data \({{{\rm{x}}}:\Omega \mapsto {\mathbb{R}}\), that is, we are interested in learning a function: $${{{\rm{aff}}}_{N}^{{{\rm{x}}}:\Omega \mapsto {[0,1]}^{| N| }$$ (2) such that \({{{\rm{...