2023 - Research.com Genetics in United States Leader Award
2022 - Research.com Best Scientist Award
2020 - ACM Fellow For contributions to computational biology, including software for DNA sequence analysis, alignment, and genome assembly
2018 - Fellow of the American Academy of Arts and Sciences
2017 - Fellow of the Indian National Academy of Engineering (INAE)
2013 - Fellow of the International Society for Computational Biology
2004 - Fellow of the American Association for the Advancement of Science (AAAS)
His primary areas of investigation include Genetics, Genome, Gene, Sequence analysis and Computational biology. His study in Microbiology extends to Genetics with its themes. His research on Genome often connects related topics like Plasmid.
His work in Sequence analysis addresses subjects such as Repeated sequence, which are connected to disciplines such as Computational problem and Range. His Computational biology research is multidisciplinary, incorporating perspectives in RNA-Seq, ENCODE, DNA, Sequence assembly and splice. His study looks at the intersection of DNA sequencing and topics like Contig Mapping with Algorithm.
Steven L. Salzberg mostly deals with Genome, Genetics, Gene, Computational biology and Genomics. His Genome research includes themes of Evolutionary biology and DNA sequencing. While the research belongs to areas of DNA sequencing, Steven L. Salzberg spends his time largely on the problem of Metagenomics, intersecting his research to questions surrounding Kraken.
Sequence analysis, Sequence assembly, Human genome, Sequence and Comparative genomics are among the areas of Genetics where Steven L. Salzberg concentrates his study. The Computational biology study combines topics in areas such as RNA-Seq, Transcriptome, Annotation, Bacterial genome size and splice. His research investigates the link between Whole genome sequencing and topics such as Microbiology that cross with problems in Virulence.
The scientist’s investigation covers issues in Genome, Computational biology, Gene, Reference genome and DNA sequencing. His research in Genome is mostly concerned with Genomics. His study in Computational biology is interdisciplinary in nature, drawing from both Genome project, Human genome, RNA, Bacterial genome size and RefSeq.
Steven L. Salzberg works mostly in the field of Gene, limiting it down to topics relating to Sequoia and, in certain cases, Plant disease resistance, as a part of the same area of interest. His Plant disease resistance study contributes to a more complete understanding of Genetics. Steven L. Salzberg has included themes like Genome size, Contig, Chromosome, Juglans and Gene Annotation in his Reference genome study.
Steven L. Salzberg focuses on Genome, Computational biology, Metagenomics, DNA sequencing and Reference genome. His Genome research integrates issues from Evolutionary biology, Amniote, Modular design, Perl and Data structure. His research integrates issues of Cerebrospinal fluid, RNA, Gene, Human genetics and RefSeq in his study of Computational biology.
In his work, Gene Annotation is strongly intertwined with Genome project, which is a subfield of DNA sequencing. His Reference genome research includes elements of Juglans sigillata, Sequence analysis, Contig and Genomics. Extramural and Human diversity are fields of study that intersect with his Human genome research.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
Fast gapped-read alignment with Bowtie 2
Ben Langmead;Steven L Salzberg;Steven L Salzberg;Steven L Salzberg.
Nature Methods (2012)
Ultrafast and memory-efficient alignment of short DNA sequences to the human genome
Ben Langmead;Cole Trapnell;Mihai Pop;Steven L Salzberg.
Genome Biology (2009)
Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation
Cole Trapnell;Cole Trapnell;Brian A Williams;Geo Pertea;Ali Mortazavi.
Nature Biotechnology (2010)
TopHat: discovering splice junctions with RNA-Seq
Cole Trapnell;Lior Pachter;Steven L. Salzberg.
TopHat2: accurate alignment of transcriptomes in the presence of insertions, deletions and gene fusions
Daehwan Kim;Daehwan Kim;Geo Pertea;Cole Trapnell;Cole Trapnell;Harold Pimentel.
Genome Biology (2013)
Differential gene and transcript expression analysis of RNA-seq experiments with TopHat and Cufflinks
Cole Trapnell;Adam Roberts;Loyal Goff;Loyal Goff;Loyal Goff;Geo Pertea.
Nature Protocols (2012)
HISAT: a fast spliced aligner with low memory requirements
Daehwan Kim;Ben Langmead;Steven L Salzberg.
Nature Methods (2015)
FLASH: Fast Length Adjustment of Short Reads to Improve Genome Assemblies
Tanja Magoč;Steven L. Salzberg.
Programs for Machine Learning
Steven L. Salzberg;Alberto Segre.
StringTie enables improved reconstruction of a transcriptome from RNA-seq reads
Mihaela Pertea;Geo M. Pertea;Corina M. Antonescu;Tsung Cheng Chang.
Nature Biotechnology (2015)
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