Tracking specific events in a program’s execution, such as object allocation or lock acquisition, is at the heart of dynamic analysis. Despite apparent simplicity this task, quantifying these challenging due to presence compiler optimizations. Profiling perturbs optimizations that would normally do—a profiled program usually behaves differently than original one. In article, we propose novel te...

Data profiling is the discipline of discovering metadata about given datasets. The metadata itself serve a variety of use cases, such as data integration, data cleansing, or query optimization. Due to the importance of data profiling in practice, many tools have emerged that support data scientists and IT professionals in this task. These tools provide good support for profiling statistics that...

Achieving performance, reliability, and scalability has proven difficult for distributed file systems. Placement of data, load distribution and other overheads are often the culprits. Profiling is a useful technique for understanding file system behavior, improving performance and debugging problems. Existing file system profiling methods often examine fine-grained system activity, such as the ...

BACKGROUND Expression profiling, the measurement of all transcripts of a cell or tissue type, is currently the most comprehensive method to describe their physiological states. Given that accurate profiling methods currently available require RNA amounts found in thousands to millions of cells, many fields of biology working with specialized cell types cannot use these techniques because availa...

Application profiling is a popular technique that attempts to understand program behavior to improve its performance. Offline profiling, although beneficial for several applications, fails in cases where prior program runs may not be feasible, or if changes in input cause the profile to not match the behavior of the actual program run. Managed languages, like Java and C#, provide a unique oppor...

In article number 2100111, Song, Yang, and co-workers summarize recent advances in single-cell transcriptome sequencing multi-dimensional profiling. The investigation of mRNA enables the interrogation gene expression pattern, revealing cell-to-cell heterogeneity. measurement, including spatially temporally resolved analysis, multi-omics profiling allows a more comprehensive overview understandi...

The nature and pace of genome mutation is largely unknown. Standard methods to investigate DNA-mutation rely on arraying or sequencing DNA from a population of cells, hence the genetic composition of individual cells is lost and de novo mutation in cell(s) is concealed within the bulk signal. We developed methods based on (SNP-) arraying and next-generation sequencing of single-cell whole-genom...