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Ehsaneddin Asgari - Deep learning
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Ehsaneddin Asgari

Deep learning
University of California System • University of California, Berkeley • Berkeley • United States of America

Skills and expertise

Fields of interest
  • De novo sequencing analysis
  • Metagenomic sequencing analysis
  • NMR-based proteomics analysis
Languages
  • English
Programming languages
  • Python

Reviews and Discussions

LATEST REVIEWS

MicroPheno 2018-06-29, 09:32:12
I am the first author of this paper and tool. This software predicts 16S rRNA phenotype using k-mer profile. So it does not have anything with taxonomy classification and homology. In addition, the…

LATEST DISCUSSIONS

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TOOLS MAINTAINED

MicroPheno

Desktop

MicroPheno

(1) 0 discussion(s)
Predicts the environment or host phenotype from microbial samples based on k-mer distributions in shallow subsamples of 16S rRNA data. MicroPheno has three principal functions such as: i) the use of…
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DiTaxa

Desktop

DiTaxa

(0) 0 discussion(s)
Serves as a method for sequence phenotype classification and biomarker detection from 16S ribosomal RNA (16S rRNA) amplicon data. DiTaxa original approach is based on the substitution of standard…

Fields of interest

De novo sequencing analysis
Optimizes the global minimal genetic distance in a given population. MITOMIX…
Maps reads against multiple reference genomes. PanVC is designed for variant…
Permits researchers to conduct investigation and construct high-quality…
Metagenomic sequencing analysis
Conducts RNA-seq read alignment and read counting from raw sequence reads to…
Categorizes organisms of interest into species by exploiting genomic…
Performs assignment for bacterial 16S and amplicon sequencing. HmmUFOtu is a…
NMR-based proteomics analysis
Automates the elimination of noise peaks. Filt Robot employs convolutional…
Assists users to perform spectra analysis. Dumpling comprises the following…
Allows users to proceed file conversions from 1D nuclear magnetic resonance…