Modern day proteomics generates ever more complex data, causing the requirements on the storage and processing of such data to outgrow the capacity of most desktop computers. To cope with the increased computational demands, distributed architectures have gained substantial popularity in the recent years. In this review, we provide an overview of the current techniques for distributed computing, along with examples of how the techniques are currently being employed in the field of proteomics. We thus underline the benefits of distributed computing in proteomics, while also pointing out the potential issues and pitfalls involved
In a global effort for scientific transparency, it has become feasible and good practice to share ex...
Machine learning is a subdiscipline within artificial intelligence that focuses on algorithms that a...
Machine learning is a subdiscipline within artificial intelligence that focuses on algorithms that a...
Modern day proteomics generates ever more complex data, causing the requirements on the storage and ...
The use of proteomics bioinformatics substantially contributes to an improved understanding of prote...
www.cs.nott.ac.uk/~{aas,dxb,nxk} Abstract. Grid and distributed public computing schemes has become ...
The booming of proteomics data has positioned multiple disciplines and research areas in a more comp...
Abstract. Grid computing has great potential for supporting the integration of complex, fast changin...
The booming of proteomics data has positioned multiple disciplines and research areas in a more comp...
Proteomics is the study of proteins and their interactions in a cell. With the completion of the Hum...
Distributed computing is a potentially very powerful approach for accessing large amounts of computa...
Abstract. The potential for Grid technologies in applied bioinformatics is largely unexplored. We ha...
Most current proteomics workflows, while highly developed and sophisticated, are usually not compati...
In large-scale proteomics studies there is a temptation, after months of experimental work, to plug ...
AbstractIn large-scale proteomics studies there is a temptation, after months of experimental work, ...
In a global effort for scientific transparency, it has become feasible and good practice to share ex...
Machine learning is a subdiscipline within artificial intelligence that focuses on algorithms that a...
Machine learning is a subdiscipline within artificial intelligence that focuses on algorithms that a...
Modern day proteomics generates ever more complex data, causing the requirements on the storage and ...
The use of proteomics bioinformatics substantially contributes to an improved understanding of prote...
www.cs.nott.ac.uk/~{aas,dxb,nxk} Abstract. Grid and distributed public computing schemes has become ...
The booming of proteomics data has positioned multiple disciplines and research areas in a more comp...
Abstract. Grid computing has great potential for supporting the integration of complex, fast changin...
The booming of proteomics data has positioned multiple disciplines and research areas in a more comp...
Proteomics is the study of proteins and their interactions in a cell. With the completion of the Hum...
Distributed computing is a potentially very powerful approach for accessing large amounts of computa...
Abstract. The potential for Grid technologies in applied bioinformatics is largely unexplored. We ha...
Most current proteomics workflows, while highly developed and sophisticated, are usually not compati...
In large-scale proteomics studies there is a temptation, after months of experimental work, to plug ...
AbstractIn large-scale proteomics studies there is a temptation, after months of experimental work, ...
In a global effort for scientific transparency, it has become feasible and good practice to share ex...
Machine learning is a subdiscipline within artificial intelligence that focuses on algorithms that a...
Machine learning is a subdiscipline within artificial intelligence that focuses on algorithms that a...