This important study, which tackles the challenge of analyzing genome integrity and instability in unicellular pathogens by introducing a novel single-cell genomics approach, presents compelling ...

Learn what is Linear Regression Cost Function in Machine Learning and how it is used. Linear Regression Cost function in Machine Learning is "error" representation between actual value and model ...

This repository contains a complete collection of implementations for various Numerical Methods used in computational mathematics. The project covers a wide range of topics including linear and ...

Abstract: Linear discriminant analysis (LDA) is a widely used technique for data classification. The method offers adequate performance in many classification problems, but it becomes inefficient when ...

This fully updated volume explores a wide array of new and state-of-the-art tools and resources for protein function prediction. Beginning with in-depth overviews of essential underlying computational ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Implementations of matrix multiplication via diffusion and reactions, thus eliminating ...

The Transformer architecture revolutionised natural language processing with its self-attention mechanism, enabling parallel computation and effective context retrieval. However, Transformers face ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. In this work, we describe the development of a new algorithm for the computation of ...

A simulation study is designed to explore the accuracy of attribute parameter estimation in the crossed random effects linear logistic test model (CRELLTM) with the impact of Q-matrix misspecification ...