Omics data contain signals from the molecular, physical, and kinetic inter-and intracellular
interactions that control biological systems. Matrix factorization (MF) techniques can reveal …

Although nonnegative matrix factorization (NMF) is widely used, some matrix factorization
methods result in misleading results and waste of computing resources due to lack of timely …

Biclustering, the simultaneous clustering of rows and columns of a data matrix, has proved
its effectiveness in bioinformatics due to its capacity to produce local instead of global …

Profound attention to MapReduce framework has been caught by many different areas. It is
presently a practical model for data-intensive applications due to its simple interface of …

We explore the trade-offs of performing linear algebra using Apache Spark, compared to
traditional C and MPI implementations on HPC platforms. Spark is designed for data …

Non-negative matrix factorization (NMF) is the problem of determining two non-negative low
rank factors W and H, for the given input matrix A, such that A≈ WH. NMF is a useful tool for …

Background: The size of genomics data has been growing rapidly over the last decade.
However, the conventional data analysis techniques are incapable of processing this huge …

The Map-Reduce model simplifies the large scale data handling on commodities group by
abusing parallel map & reduces assignments.. The use of this model is beneficial only when …

Non-negative matrix factorization (NMF) is the problem of determining two non-negative low
rank factors Wand H, for the given input matrix A, such that A WH. NMF is a useful tool for …

With the evolution of Internet standards and advancements in various Internet and mobile
technologies, especially since web 4.0, more and more web and mobile applications …