What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Programming language
- Software
Falk Schreiber focuses on Biological network, Theoretical computer science, Software, Systems biology and Network motif.
His study on Biological network is covered under Computational biology.
His Theoretical computer science study combines topics in areas such as Ranking and Centrality.
His studies deal with areas such as Visualization and SBML as well as Software.
Falk Schreiber has researched SBML in several fields, including Programming language and Systems Biology Graphical Notation.
His research in Systems Biology Graphical Notation intersects with topics in BioPAX : Biological Pathways Exchange, Data flow diagram, Unified Modeling Language, Knowledge representation and reasoning and Query language.
His most cited work include:
- The Systems Biology Graphical Notation (670 citations)
- The Systems Biology Graphical Notation (670 citations)
- VANTED: A system for advanced data analysis and visualization in the context of biological networks (390 citations)
What are the main themes of his work throughout his whole career to date?
Falk Schreiber spends much of his time researching Visualization, Biological network, Systems biology, Data science and Theoretical computer science.
His work carried out in the field of Visualization brings together such families of science as Software, Human–computer interaction and Biological data.
Falk Schreiber has included themes like World Wide Web and SBML in his Software study.
His Biological network research is multidisciplinary, incorporating perspectives in Data mining, Computer graphics and Systems Biology Graphical Notation.
He works mostly in the field of Data science, limiting it down to concerns involving Visual analytics and, occasionally, Information visualization.
His Theoretical computer science research is multidisciplinary, relying on both Centrality, Set and Graph.
He most often published in these fields:
- Visualization (38.93%)
- Biological network (44.29%)
- Systems biology (35.36%)
What were the highlights of his more recent work (between 2018-2021)?
- Visualization (38.93%)
- Systems biology (35.36%)
- Data science (28.93%)
In recent papers he was focusing on the following fields of study:
His main research concerns Visualization, Systems biology, Data science, Human–computer interaction and Variety.
His Visualization research includes elements of Semantics and Biological network.
While the research belongs to areas of Biological network, Falk Schreiber spends his time largely on the problem of Artificial intelligence, intersecting his research to questions surrounding Ic50 values.
His studies in Systems biology integrate themes in fields like SBML, Integrative bioinformatics, Synthetic biology, Software and Software engineering.
His Data science research incorporates elements of Field, Relevance and Interoperability.
His work deals with themes such as Domain, Data visualization and Focus, which intersect with Variety.
Between 2018 and 2021, his most popular works were:
- COVID-19 Disease Map, building a computational repository of SARS-CoV-2 virus-host interaction mechanisms. (51 citations)
- COVID-19 Disease Map, building a computational repository of SARS-CoV-2 virus-host interaction mechanisms. (51 citations)
- SBML Level 3: an extensible format for the exchange and reuse of biological models (42 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Programming language
- Database
Systems biology, Visualization, Computational biology, Software engineering and SBML are his primary areas of study.
His work in the fields of Systems biology, such as Systems Biology Graphical Notation, intersects with other areas such as Entity–relationship model.
The study incorporates disciplines such as Analytics, Relation and Virtual reality, Human–computer interaction in addition to Visualization.
His Computational biology research spans across into subjects like Viral immunology, Coronavirus Infections, Virus-host interaction, Severe acute respiratory syndrome coronavirus 2 and Pandemic.
His Software engineering research incorporates themes from CellML, BioPAX : Biological Pathways Exchange, Synthetic biology and Integrative bioinformatics.
His SBML research is multidisciplinary, incorporating elements of Software, File format, Computational model and Interoperability.
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