[go: up one dir, main page]
More Web Proxy on the site http://driver.im/

Kannan et al., 2016 - Google Patents

Shannon: an information-optimal de novo RNA-Seq assembler

Kannan et al., 2016

View PDF
Document ID
3399018553271010819
Author
Kannan S
Hui J
Mazooji K
Pachter L
Tse D
Publication year
Publication venue
BioRxiv

External Links

Snippet

De novo assembly of short RNA-Seq reads into transcripts is challenging due to sequence similarities in transcriptomes arising from gene duplications and alternative splicing of transcripts. We present Shannon, an RNA-Seq assembler with an optimality guarantee …
Continue reading at www.biorxiv.org (PDF) (other versions)

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/10Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology
    • G06F19/22Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology for sequence comparison involving nucleotides or amino acids, e.g. homology search, motif or SNP [Single-Nucleotide Polymorphism] discovery or sequence alignment
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/10Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology
    • G06F19/24Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology for machine learning, data mining or biostatistics, e.g. pattern finding, knowledge discovery, rule extraction, correlation, clustering or classification
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/10Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology
    • G06F19/18Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology for functional genomics or proteomics, e.g. genotype-phenotype associations, linkage disequilibrium, population genetics, binding site identification, mutagenesis, genotyping or genome annotation, protein-protein interactions or protein-nucleic acid interactions
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/10Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology
    • G06F19/20Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology for hybridisation or gene expression, e.g. microarrays, sequencing by hybridisation, normalisation, profiling, noise correction models, expression ratio estimation, probe design or probe optimisation
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N27/00Investigating or analysing materials by the use of electric, electro-chemical, or magnetic means
    • G01N27/26Investigating or analysing materials by the use of electric, electro-chemical, or magnetic means by investigating electrochemical variables; by using electrolysis or electrophoresis
    • G01N27/416Systems
    • G01N27/447Systems using electrophoresis
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00Investigating or analysing materials by specific methods not covered by the preceding groups
    • G01N33/48Investigating or analysing materials by specific methods not covered by the preceding groups biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing

Similar Documents

Publication Publication Date Title
Kannan et al. Shannon: an information-optimal de novo RNA-Seq assembler
Haas et al. STAR-Fusion: fast and accurate fusion transcript detection from RNA-Seq
Jones et al. MetaPSICOV: combining coevolution methods for accurate prediction of contacts and long range hydrogen bonding in proteins
Ye et al. DBG2OLC: efficient assembly of large genomes using long erroneous reads of the third generation sequencing technologies
Iyer et al. The landscape of long noncoding RNAs in the human transcriptome
Ghandi et al. Enhanced regulatory sequence prediction using gapped k-mer features
Trigg et al. Multicoil2: predicting coiled coils and their oligomerization states from sequence in the twilight zone
Chung et al. Discovering transcription factor binding sites in highly repetitive regions of genomes with multi-read analysis of ChIP-Seq data
Kamal et al. De-Bruijn graph with MapReduce framework towards metagenomic data classification
Lin et al. CLIIQ: Accurate comparative detection and quantification of expressed isoforms in a population
Savino et al. Differential co-expression analyses allow the identification of critical signalling pathways altered during tumour transformation and progression
Futschik et al. Multiscale DNA partitioning: statistical evidence for segments
Goussarov et al. Introduction to the principles and methods underlying the recovery of metagenome‐assembled genomes from metagenomic data
Wang et al. A de Bruijn graph approach to the quantification of closely-related genomes in a microbial community
Kritikos et al. Noise reduction in protein-protein interaction graphs by the implementation of a novel weighting scheme
Rautiainen et al. AERON: Transcript quantification and gene-fusion detection using long reads
Li et al. Bayesian model of protein primary sequence for secondary structure prediction
Dufault‐Thompson et al. Applications of de Bruijn graphs in microbiome research
Bruford et al. Devising a consensus framework for validation of novel human coding loci
Zhang et al. Biobank-scale inference of ancestral recombination graphs enables genealogy-based mixed model association of complex traits
Wajid et al. The A, C, G, and T of genome assembly
Bhattacharya et al. FRAGSION: ultra-fast protein fragment library generation by IOHMM sampling
Vasimuddin et al. Identification of significant computational building blocks through comprehensive investigation of NGS secondary analysis methods
White III et al. MerCat: a versatile k-mer counter and diversity estimator for database-independent property analysis obtained from metagenomic and/or metatranscriptomic sequencing data
González et al. VTAM: A robust pipeline for validating metabarcoding data using internal controls