Channels :: FRELIP Discovery

Author: Mulder, Nicola

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Identification of the virulence gene of Mycobacterium tuberculosis

Similar Items: Identification of the virulence gene of Mycobacterium tuberculosis

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Characterisation of the metabolome of Mycobacterium tuberculosis to identify new pathways and pathway holes
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Genome-Wide Associations Between Human Genotypes and Mycobacterium tuberculosis Clades Causing Disease
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Prevalence and frequency spectra of single nucleotide polymorphisms at exon-intron junctions of human genes
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The identification of cytotoxic T lymphocyte (CTL) escape in a large, longitudinal subtype C HIV-1 sequence dataset
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Transcription analysis of virulent strains of Mycobacterium tuberculosis
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Regulatory networks in non-small cell lung cancer: Connecting differentially expressed genes, miRNAs, and incRNAs
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A bioinformatic study on the feasibility of a cross-species proteomics analyses of mycobacteria
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Regulated T cell pre-mRNA splicing as genetic marker of T cell suppression
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Network-based approach for post genome-wide association study analysis in admixed populations
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Integration and visualisation of data in bioinformatics
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Evaluating the predictive performance of cytotoxic T lymphocyte epitope prediction tools using Elispot assay data
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Influence of gut microbiota on immune system in infants
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The evolutionary impacts of secondary structures within genomes of eukaryote-infecting single-stranded DNA viruses
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Creating and analysing an African pan-genome
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Impact of the mycobiome on the health of the female genital tract
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Investigation of HIV-TB co-infection through analysis of the potential impact of host genetic variation on host-pathogen protein interactions
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Revisiting and re-computing the X-score scoring function
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Computational Identification of Circulating MicroRNAs Associated with the Early Stage of Ovarian Cancer
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Evaluation of single nucleotide polymorphisms in virulence genes of Mycobacterium tuberculosis as markers of lineages and sub-lineages in Tshwane region
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Identification of Novel Argonaute Proteins Using a Metagenomic Mining Approach