What is he best known for?
The fields of study he is best known for:
- Gene
- Artificial intelligence
- Programming language
Michael Schroeder mainly focuses on Bioinformatics, Protein structure, Computational biology, Information retrieval and Genetics.
His Bioinformatics research is multidisciplinary, relying on both Plasma protein binding, Web service, Data mining, Source code and Software.
His Protein structure research is multidisciplinary, incorporating perspectives in Protein domain, Database, Sequence alignment and Binding site.
His studies in Computational biology integrate themes in fields like Lipidome, Shotgun, Drug repositioning, DNA microarray and Drug discovery.
His study in the field of Search engine indexing and Ontology also crosses realms of Mass spectrum.
His Ontology study combines topics from a wide range of disciplines, such as Controlled vocabulary and Gene ontology.
His most cited work include:
- PLIP: fully automated protein–ligand interaction profiler (556 citations)
- GoPubMed : exploring pubMed with the Gene Ontology (441 citations)
- LIGSITEcsc: predicting ligand binding sites using the Connolly surface and degree of conservation (363 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of study are Computational biology, Information retrieval, Ontology, Artificial intelligence and World Wide Web.
The Computational biology study combines topics in areas such as Genetics, Protein–protein interaction, Drug repositioning, DNA microarray and Protein structure.
His research in Protein structure intersects with topics in Binding site and Sequence alignment.
His research combines Text mining and Information retrieval.
His Ontology research incorporates themes from Ontology and Controlled vocabulary.
His Artificial intelligence study incorporates themes from Machine learning and Natural language processing.
He most often published in these fields:
- Computational biology (17.51%)
- Information retrieval (14.40%)
- Ontology (12.84%)
What were the highlights of his more recent work (between 2015-2021)?
- Computational biology (17.51%)
- Drug repositioning (6.61%)
- Drug (4.67%)
In recent papers he was focusing on the following fields of study:
Michael Schroeder focuses on Computational biology, Drug repositioning, Drug, Protein structure and Amino acid.
Michael Schroeder carries out multidisciplinary research, doing studies in Computational biology and Network analysis.
His study in Drug repositioning is interdisciplinary in nature, drawing from both Cancer research, Chagas disease and Drug discovery.
His work on Drug development as part of general Drug study is frequently linked to Structure based, therefore connecting diverse disciplines of science.
His work on Protein Data Bank as part of general Protein structure research is frequently linked to Glycan, thereby connecting diverse disciplines of science.
He studied Amino acid and Sequence that intersect with Stereochemistry and Sequence alignment.
Between 2015 and 2021, his most popular works were:
- Pioneering topological methods for network-based drug-target prediction by exploiting a brain-network self-organization theory. (39 citations)
- UniLectin3D, a database of carbohydrate binding proteins with curated information on 3D structures and interacting ligands (31 citations)
- New HSP27 inhibitors efficiently suppress drug resistance development in cancer cells (30 citations)
In his most recent research, the most cited papers focused on:
- Gene
- Artificial intelligence
- Programming language
Michael Schroeder spends much of his time researching Drug repositioning, Protein structure, Drug, Computational biology and Binding site.
He interconnects Amino acid, Function, Protein biosynthesis, Structural motif and Stereochemistry in the investigation of issues within Protein structure.
His Drug research includes themes of Chagas disease and Neglected Disease.
Michael Schroeder works on Computational biology which deals in particular with Systems biology.
His Binding site research is multidisciplinary, incorporating elements of Structure–activity relationship, Protein Data Bank and Enzyme.
His Pharmacology study deals with Heat shock protein intersecting with Drug resistance.
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