[go: up one dir, main page]

Claverie, 2000 - Google Patents

From bioinformatics to computational biology

Claverie, 2000

View PDF @Free from Publisher
Document ID
7621703094337007886
Author
Claverie J
Publication year
Publication venue
Genome research

External Links

Snippet

It is quite ironic that the uncertainty about the number of human genes (28,000– 120,000)(Ewing and Green 2000; Liang et al. 2000; Roest Crollius et al. 2000) appears to increase as the determination of the human genome sequence is nearing completion. I shall …
Continue reading at genome.cshlp.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
    • G06F19/28Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology for programming tools or database systems, e.g. ontologies, heterogeneous data integration, data warehousing or computing architectures
    • 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
    • G06F19/12Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology for modelling or simulation in systems biology, e.g. probabilistic or dynamic models, gene-regulatory networks, protein interaction networks or metabolic networks
    • 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
    • G06F19/16Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology for molecular structure, e.g. structure alignment, structural or functional relations, protein folding, domain topologies, drug targeting using structure data, involving two-dimensional or three-dimensional structures
    • 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
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F9/00Arrangements for programme control, e.g. control unit
    • G06F9/06Arrangements for programme control, e.g. control unit using stored programme, i.e. using internal store of processing equipment to receive and retain programme
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/20Handling natural language data
    • CCHEMISTRY; METALLURGY
    • C12BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12NMICRO-ORGANISMS OR ENZYMES; COMPOSITIONS THEREOF; PROPAGATING, PRESERVING OR MAINTAINING MICRO-ORGANISMS; MUTATION OR GENETIC ENGINEERING; CULTURE MEDIA
    • C12N15/00Mutation or genetic engineering; DNA or RNA concerning genetic engineering, vectors, e.g. plasmids, or their isolation, preparation or purification; Use of hosts therefor
    • C12N15/09Recombinant DNA-technology
    • C12N15/10Processes for the isolation, preparation or purification of DNA or RNA
    • C12N15/1034Isolating an individual clone by screening libraries
    • CCHEMISTRY; METALLURGY
    • C12BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12QMEASURING OR TESTING PROCESSES INVOLVING ENZYMES OR MICRO-ORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q1/00Measuring or testing processes involving enzymes, nucleic acids or micro-organisms; Compositions therefor; Processes of preparing such compositions
    • C12Q1/68Measuring or testing processes involving enzymes, nucleic acids or micro-organisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
    • C12Q1/6869Methods for sequencing

Similar Documents

Publication Publication Date Title
Wei et al. Computational prediction and interpretation of cell-specific replication origin sites from multiple eukaryotes by exploiting stacking framework
Aoki et al. Convolutional neural networks for classification of alignments of non-coding RNA sequences
Dao et al. Identify origin of replication in Saccharomyces cerevisiae using two-step feature selection technique
Zhang et al. CRIP: predicting circRNA–RBP-binding sites using a codon-based encoding and hybrid deep neural networks
Chen et al. MethyRNA: a web server for identification of N6-methyladenosine sites
Feng et al. iDNA6mA-PseKNC: Identifying DNA N6-methyladenosine sites by incorporating nucleotide physicochemical properties into PseKNC
Qiang et al. M6AMRFS: robust prediction of N6-methyladenosine sites with sequence-based features in multiple species
Zhang et al. RBPPred: predicting RNA-binding proteins from sequence using SVM
Schweikert et al. mGene: accurate SVM-based gene finding with an application to nematode genomes
Zorita et al. Starcode: sequence clustering based on all-pairs search
Pham et al. H2Opred: a robust and efficient hybrid deep learning model for predicting 2’-O-methylation sites in human RNA
Zhang et al. Predicting CTCF-mediated chromatin loops using CTCF-MP
Claverie From bioinformatics to computational biology
Li et al. HSM6AP: a high-precision predictor for the Homo sapiens N6-methyladenosine (m^ 6 A) based on multiple weights and feature stitching
Zeng et al. LncLocFormer: a transformer-based deep learning model for multi-label lncRNA subcellular localization prediction by using localization-specific attention mechanism
Huang et al. Weakly supervised learning of RNA modifications from low-resolution epitranscriptome data
Cui et al. Protein–DNA/RNA interactions: Machine intelligence tools and approaches in the era of artificial intelligence and big data
Brejová et al. Finding patterns in biological sequences
Jiang et al. Basics of bioinformatics: Lecture notes of the graduate summer school on bioinformatics of China
Metzner et al. Multiome Perturb-seq unlocks scalable discovery of integrated perturbation effects on the transcriptome and epigenome
Liu et al. CAKE: a flexible self-supervised framework for enhancing cell visualization, clustering and rare cell identification
Reddy et al. HybridPPI: A Hybrid Machine Learning Framework for Protein-Protein Interaction Prediction
Song et al. Multi-task adaptive pooling enabled synergetic learning of RNA modification across tissue, type and species from low-resolution epitranscriptomes
Si et al. Improved protein contact prediction using dimensional hybrid residual networks and singularity enhanced loss function
Alam et al. Unveiling the potential pattern representation of rna 5-methyluridine modification sites through a novel feature fusion model leveraging convolutional neural network and tetranucleotide composition