The phrase "and datasets in a" is correct and usable in written English.
It can be used when discussing various types of data or information, particularly in contexts related to data analysis, research, or technology.
Example: "The study focuses on the integration of machine learning algorithms and datasets in a comprehensive framework for data analysis."
Alternatives: "and data collections in a" or "and data sets within a".
One successful attempt to address these is by integrating diverse approaches and datasets in a comprehensive manner that may substantially improve animal MTIs prediction.
Good metadata allows future users of a dataset to understand how it was created and how to integrate it with other processes and datasets in a scientifically sound approach.
It provides a simple way to encapsulate computational tools and datasets in a graphical user interface (GUI), together with a mechanism to keep track of the execution history in a reproducible manner.
It also might undermine integration of the new genomic methods and datasets in an effort to unravel the function of lncRNA.
These systems should also provide computational tools for the analysis of new genomic and metagenomic datasets in a fast and accurate way.
With the combined power of ADAM and Mango, you can load, query, and explore datasets in a unified environment.
Since the Sotiriou, Desmedt and Miller datasets have some patients in common, we merged the Sotiriou and Desmedt datasets in a single dataset, from which we removed the patients included in the Miller dataset.
This dataset was split into training and testing datasets in a 2 1 ratio.
Firstly, it is iterative which means that it allows each piece of data to contribute as both training and validation datasets in an iterative manner and summarizes the results as the average of different iterations.
To solve this problem, we have created SeqPig, a library and a collection of tools to manipulate, analyze and query sequencing datasets in a scalable and simple manner.
We describe a framework, called DataCutter, that is designed to provide support for subsetting and processing of datasets in a distributed and heterogeneous environment.
