What is he best known for?
The fields of study he is best known for:
The scientist’s investigation covers issues in Ribosomal RNA, Database, Genetics, Phylogenetic tree and Phylogenetics.
His work deals with themes such as Terminal restriction fragment length polymorphism, Sequence database and 16S ribosomal RNA, which intersect with Ribosomal RNA.
His Database study combines topics in areas such as Small subunit, Visualization, The Internet and Ribosome.
His work in Genetics addresses issues such as Computational biology, which are connected to fields such as DNA sequencing and Sequence analysis.
His Phylogenetics research is multidisciplinary, incorporating perspectives in Bacteria, Aerobic bacteria, Myxobacteria and Fermentation.
The various areas that he examines in his Earth Microbiome Project study include Bioinformatics, Classifier, Bacterial taxonomy, Bayes' theorem and UniFrac.
His most cited work include:
- Naïve Bayesian Classifier for Rapid Assignment of rRNA Sequences into the New Bacterial Taxonomy (11186 citations)
- The Ribosomal Database Project: improved alignments and new tools for rRNA analysis (3883 citations)
- Ribosomal Database Project: data and tools for high throughput rRNA analysis (2297 citations)
What are the main themes of his work throughout his whole career to date?
James R. Cole mainly focuses on Computational biology, Metagenomics, Gene, Ribosomal RNA and Genetics.
His research on Computational biology also deals with topics like
- Sequence analysis that connect with fields like Restriction fragment,
- DNA sequencing which connect with Sequence.
James R. Cole interconnects Ecology, Marker gene, Bioinformatics and Genomics in the investigation of issues within Metagenomics.
His Bioinformatics research includes themes of Classifier and UniFrac.
His Ribosomal RNA research is multidisciplinary, incorporating elements of Database and Phylogenetic tree.
His work on Identification as part of general Database research is often related to Pipeline, thus linking different fields of science.
He most often published in these fields:
- Computational biology (23.73%)
- Metagenomics (23.73%)
- Gene (22.03%)
What were the highlights of his more recent work (between 2017-2021)?
- Ecology (15.25%)
- Gene (22.03%)
- Computational biology (23.73%)
In recent papers he was focusing on the following fields of study:
His primary scientific interests are in Ecology, Gene, Computational biology, Ecosystem and Tundra.
His study focuses on the intersection of Gene and fields such as Bacteria with connections in the field of Extracellular and Biochemistry.
James R. Cole performs multidisciplinary study in Computational biology and Prioritization in his work.
His Genome research incorporates elements of Transfer RNA, 16S ribosomal RNA and CRISPR.
As part of one scientific family, he deals mainly with the area of 16S ribosomal RNA, narrowing it down to issues related to the Taxon, and often Pseudomonas, Species diversity, Ribosomal RNA, Range and Evolutionary biology.
His Bacterial genome size research includes elements of Bacterial Physiological Phenomena and Database, Identification.
Between 2017 and 2021, his most popular works were:
- The Microbial Genomes Atlas (MiGA) webserver: taxonomic and gene diversity analysis of Archaea and Bacteria at the whole genome level (170 citations)
- ARGs-OAP v2.0 with an expanded SARG database and Hidden Markov Models for enhancement characterization and quantification of antibiotic resistance genes in environmental metagenomes. (85 citations)
- RNAcentral: a hub of information for non-coding RNA sequences (82 citations)
In his most recent research, the most cited papers focused on:
James R. Cole spends much of his time researching Gene, Computational biology, Genome, 16S ribosomal RNA and Non-coding RNA.
His Computational biology research integrates issues from Genome browser, Clade, Archaea, Bacteria and Microbial Genomes.
His research in 16S ribosomal RNA intersects with topics in Taxon, Sequence analysis, Drug resistance and Hidden Markov model.
His Taxon research is multidisciplinary, incorporating elements of Evolutionary biology, Range, Ribosomal RNA, Species diversity and Pseudomonas.
His research investigates the link between Antibiotic resistance genes and topics such as Bacterial Physiological Phenomena that cross with problems in Metagenomics.
His studies deal with areas such as Database, Identification, Microbial genetics, Antibiotic resistance and Bacterial genome size as well as Metagenomics.
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