Tools

Computational Biology // Massey University

Knowledge-Bases


IRNdb: The database for immunologically relevant ncRNAs. IRNdb is a database that combines non-coding RNA information with immunologically relevant murine target genes. The database is intended to advance research on the influence of ncRNAs on immunological processes. ()

dPORE-miRNA: Dragon database on Polymorphic Regulation of human miRNA genes. dPORE is a database that integrates information from promoter regions of human miRNA genes, SNPs, and predicted TFBSs in the promoter regions. The web-interface allows exploring the effect of SNPs on the transcriptional regulation of miRNA genes. ()

TcoF-DB v2: Update of the database of human and mouse transcription co-factors and transcription factor interactions. TcoF-DB v2 is a database that facilitates the exploration of genes involved in the regulation of transcription in humans and mice by binding to regulatory DNA regions (transcription factors) and genes involved in the regulation of transcription by interacting with transcription factors but not binding to regulatory DNA regions (transcription co-factors). ()

TcoF-DB: Dragon database for human transcription co-factors and transcription factor interacting proteins. TcoF-DB is a database that facilitates the exploration of proteins involved in the regulation of transcription in humans by binding to regulatory DNA regions (transcription factors) and proteins involved in the regulation of transcription in humans by interacting with transcription factors and not binding to regulatory DNA regions (transcription co-factors). ()

DDPC: Dragon Database of Genes associated with Prostate Cancer. Expert reviewed information summary about the genes implicated in prostate cancer, including comprehensive information about every specific gene. DDPC provides a centralized resource for researchers to support functional characterization and analysis of molecular processes related to prostate cancer. ()

TBvis 2.0. Visualization of expression graphs for genes of the CAGE macrophage activation and M.tb infection experiment. Used for internal purposes. ()

CRCvis. Visualization of data associated to our colorectal cancer study in collaboration with Dr. Rachel Purcell

Software


NGS workflows. Some of our workflows have been made public. Check them out. They are under active development and can change without notice. Check the versioning to use stable or most up to date ones.

refseq2kraken. Download genomic reference sequences and change their headers so that Kraken is able to process them for building new Kraken databases. This was made necessary because NCBI retired GI numbers, on which Kraken relies.

MACAT: MicroArray chromosome Analysis Tool. This library contains functions to investigate links between differential gene expression and the chromosomal localization of genes. MACAT is motivated by the common observation of phenomena involving large chromosomal regions in tumor cells. MACAT is the implementation of a statistical approach for identifying significantly differentially expressed chromosome regions. ()

beanplot. Simple but customizable beanplots from the command-line.

Retired Tools


TBvis. Visualization of expression graphs for genes of the CAGE macrophage activation and M.tb infection experiment. ()

DDEC: Dragon database of genes implicated in esophageal cancer. Dragon database of genes implicated in esophageal cancer. Expert reviewed information summary about the genes implicated in esophageal cancer, including comprehensive information about every specific gene. DDEC provides a centralized resource for researchers to support functional characterization and analysis of molecular processes related to esophageal cancer. ()

DDOC: Database for exploration of functional context of genes implicated in ovarian cancer. DDOC provides a comprehensive compilation of the published research related to the genes associated with OC. Many aspects of the information provided in the DDOC were curated by biologists, which emphasize its accuracy. DDOC provides details of the cell line, tissue or cell type, expression status, disease stage, tumor grade, OC type and laboratory method provided in the literature. The links to the relevant sources of data used to extract information related to genes are also included. DDOC is freely accessible for academic and non-profit users. ()

Contact

Dr. Sebastian Schmeier
Research Group Leader
Senior Lecturer in Bioinformatics/Genomics

Massey University
Auckland, New Zealand
+64 9 414 0800 (ext: 43538)

Publications // latest

MinION Sequencing of colorectal cancer tumour microbiomes – a comparison with amplicon-based and RNA-Sequencing. PLoS One, 2020, accepted.

Molecular subtyping improves prognostication of Stage 2 colorectal cancer. BMC Cancer, 2019, 19, 1155

DeePEL: Deep learning architecture to recognize p-lncRNA and e-lncRNA promoters. In proceedings: IEEE International Conference on Bioinformatics and Biomedicine, 2019, B516, accepted.

News&Blog // latest

[ 20190528 | news ] Recent funding successes.

[ 20190319 | news ] New publication: Frontiers in Immonology

[ 20190122 | news ] New publication: BMC Genomics

[ 20181230 | news ] New publication: Molecular Phylogenetics and Evolution

[ 20180703 | news ] New publication: Nature Methods

Tweets // latest