Computer Science Research Works

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http://hdl.handle.net/1903/1593

 

Recent Submissions

  • Scaffolding of long read assemblies using long range contact information 

    Ghurye, Jay; Pop, Mihai; Koren, Sergey; Bickhart, Derek; Chin, Chen-Shan (Springer Nature, 2017-07-12)
    Long read technologies have revolutionized de novo genome assembly by generating contigs orders of magnitude longer than that of short read assemblies. Although assembly contiguity has increased, it usually does not ...
  • Transcriptome analyses reveal SR45 to be a neutral splicing regulator and a suppressor of innate immunity in Arabidopsis thaliana 

    Zhang, Xiao-Ning; Shi, Yifei; Powers, Jordan J.; Gowda, Nikhil B.; Zhang, Chong; Ibrahim, Heba M. M.; Ball, Hannah B.; Chen, Samuel L.; Lu, Hua; Mount, Stephen M. (Springer Nature, 2017-10-11)
    Regulation of pre-mRNA splicing diversifies protein products and affects many biological processes. Arabidopsis thaliana Serine/Arginine-rich 45 (SR45), regulates pre-mRNA splicing by interacting with other regulatory ...
  • Outlier detection in BLAST hits 

    Shah, Nidhi; Altschul, Stephen F.; Pop, Mihai (Springer Nature, 2018-03-22)
    An important task in a metagenomic analysis is the assignment of taxonomic labels to sequences in a sample. Most widely used methods for taxonomy assignment compare a sequence in the sample to a database of known sequences. ...
  • Yanagi: Fast and interpretable segment-based alternative splicing and gene expression analysis 

    Gunady, Mohamed K; Mount, Stephen M; Bravo, Héctor Corrada (Springer Nature, 2019-08-13)
    Ultra-fast pseudo-alignment approaches are the tool of choice in transcript-level RNA sequencing (RNA-seq) analyses. Unfortunately, these methods couple the tasks of pseudo-alignment and transcript quantification. This ...
  • MetaCarvel: linking assembly graph motifs to biological variants 

    Ghurye, Jay; Treangen, Todd; Fedarko, Marcus; Hervey, W. Judson IV; Pop, Mihai (Springer Nature, 2019-08-26)
    Reconstructing genomic segments from metagenomics data is a highly complex task. In addition to general challenges, such as repeats and sequencing errors, metagenomic assembly needs to tolerate the uneven depth of coverage ...

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