What is he best known for?
The fields of study he is best known for:
- Operating system
- Software
- Programming language
Vladimir Filkov spends much of his time researching Software development, Software quality, Knowledge management, Process and Data mining.
Vladimir Filkov has included themes like Python, Commercial software, Phenomenon and Social network in his Software development study.
His work carried out in the field of Software quality brings together such families of science as Latency, Continuous integration and Software construction.
His studies in Knowledge management integrate themes in fields like Regression analysis and Open source software.
World Wide Web is closely connected to Software maintenance in his research, which is encompassed under the umbrella topic of Process.
His Data mining research integrates issues from Consensus clustering, Microarray analysis techniques, Set and Clustering high-dimensional data.
His most cited work include:
- Fair and balanced?: bias in bug-fix datasets (265 citations)
- Latent social structure in open source projects (239 citations)
- Discovery of Rare Mutations in Populations: TILLING by Sequencing (229 citations)
What are the main themes of his work throughout his whole career to date?
Vladimir Filkov mostly deals with Software development, Software, Data science, Gene and Software quality.
His biological study spans a wide range of topics, including Software engineering, Software deployment, Knowledge management and Social network.
His Software research is multidisciplinary, incorporating elements of Focus, Process and Source code.
His study in Data science is interdisciplinary in nature, drawing from both Centrality and Resolution.
As a part of the same scientific study, Vladimir Filkov usually deals with the Gene, concentrating on Computational biology and frequently concerns with Network model, Organism and Cluster analysis.
His Software quality study combines topics from a wide range of disciplines, such as Maintainability, Code, Continuous integration and Software construction.
He most often published in these fields:
- Software development (18.81%)
- Software (16.83%)
- Data science (15.84%)
What were the highlights of his more recent work (between 2017-2020)?
- Data science (15.84%)
- Variety (5.94%)
- Software (16.83%)
In recent papers he was focusing on the following fields of study:
His main research concerns Data science, Variety, Software, Gene and Resolution.
His work on Analytics as part of general Data science study is frequently connected to Context, therefore bridging the gap between diverse disciplines of science and establishing a new relationship between them.
His research in Software intersects with topics in Mobile apps and Source code.
His Cell biology research extends to Gene, which is thematically connected.
His Resolution research incorporates elements of Scale and Visibility.
His work deals with themes such as Epigenetics and Genomics, which intersect with Gene expression.
Between 2017 and 2020, his most popular works were:
- Multiple feedback loops of the Arabidopsis circadian clock provide rhythmic robustness across environmental conditions. (35 citations)
- Social Synchrony on Complex Networks (33 citations)
- One size does not fit all: an empirical study of containerized continuous deployment workflows (18 citations)
In his most recent research, the most cited papers focused on:
- Operating system
- Software
- Programming language
His scientific interests lie mostly in Cell biology, Gene, Software engineering, Phenotype and Arabidopsis.
The various areas that Vladimir Filkov examines in his Cell biology study include Gene expression, Gene expression profiling, Genomics, Regulation of gene expression and Transcription.
Epigenetics and Gene regulatory network are among the areas of Gene where the researcher is concentrating his efforts.
His Software engineering research is multidisciplinary, incorporating perspectives in Reuse, Code reuse, Clone, Process and Flexibility.
Vladimir Filkov combines subjects such as Circadian clock, Transcription factor, Transcriptional regulation and Mutant with his study of Phenotype.
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