pSTR: identify duplications of protein short tandem repeats (pSTRs) in protein families. Mier and Andrade-Navarro, 2023
polyXY: find regions of two amino acid types (polyXY) in datasets of protein sequences. Mier et al., 2022
iOrME: sequence clusters of insect odorant receptors. Mier et al., 2022
seqQscorer: automated quality control of NGS data using machine learning. Albrecht et al., 2021 Sprang et al., 2022
PolyX2: find homorepeats in datasets of protein sequences. Mier and Andrade-Navarro, 2022
LipiDisease: associate lipids with diseases. More et al., 2021
REP2: identify protein tandem repeats. Kamel et al., 2021
DiseaseLinc: associate lincRNAs with diseases. More et al., 2021
NGS Guidelines: Quality control guidelines for NGS data files. Sprang et al., 2021
LCT: represent the distribution of repeatability versus compositional bias in a protein sequence. Mier and Andrade, 2020
MIPPIE: study and filter the network of mouse protein-protein interaction data. Alanis-Lobato et al., 2020
MAGA: analyses amino acid conservation in user defined groups of proteins from a multiple sequence alignment. Mier et al., 2020
sQanner: evaluate the distribution of polyQ stretches in a set of proteins. Mier et al., 2020
RES: scan a protein sequence for its repeatability. Kamel et al., 2019
ProteinPathTracker: find orthologs selected to study the evolutionary path of a protein. Mier et al., 2018
AnABlast: detects potential coding regions in DNA by sequence comparison. Rubio et al., 2019
Traitpedia: is a collaborative database of species traits. Mier and Andrade-Navarro, 2018
GAPI: explores a hyperbolic mapping of the human potein interaction network. Alanis-Lobato et al., 2018
HIPPIE: study and filter the network of human protein-protein interaction data. Alanis-Lobato et al., 2017
dAPE: annotates homorepeats (polyX) in protein sequence alignments. Mier and Andrade-Navarro, 2016
GeneSet2Diseases: calculates enrichment of associations to diseases on sets of human genes. Andrade-Navarro and Fontaine, 2016.
CABRA: Clusters and annotates the results of a BLAST search. Mier and Andrade-Navarro, 2016b.
FastaHerder2: uses clustering for analysis of protein similarity. Mier and Andrade-Navarro, 2016a.
OrthoFind: obtains the orthologs and paralogs of a protein sequence. Mier et al., 2015
mBISON: to find enrichment of miRNA targets on lists of genes. Gebhardt et al., 2015
CAFE: detects chromosomal abnormalities from DNA microarray expression data. Bollen et al. 2014
NYCE: predicts subcellular location of eukaryotic proteins based on their sequence. Mer and Andrade-Navarro, 2013
ARD2: identification of alpha-solenoid repeats (e.g. HEAT, armadillo) in protein sequences using a neural network. Fournier et al., 2013. ARD2 is an update of ARD: Palidwor et al., 2009
uORFdb: a literature database on upstream open reading frame (uORF) biology. Wethmar et al., 2013
CellFinder: study annotations, bibliography, gene and protein expression in stem cells and derivatives. Stachelscheid et al., 2013
PESCADOR: extract and analyse a network of gene and protein interactions from a set of Medline abstracts. Barbosa-Silva et al., 2011
QiSampler: evaluate alternative scoring schemes for list of items (e.g. genes) based on a very small set of positives. Fontaine et al., 2011
Génie: ranking all the genes of your favorite species for any topic in a few seconds using orthology information. Fontaine et al., 2011
MedlineRanker: flexible ranking of the biomedical literature in practical time. This tool allows searching the Medline database or filter a large set of abstracts for a given topic. Fontaine et al., 2009
Genes2Diseases: predict genes associated to inherited disease. Tremblay et al., 2008
pSILAC: database of proteomics measurements under the influence of various miRNAs. Selbach et al., 2008
K2D2: predict protein secondary structure content from circular dichroism spectra. Perez-Iratxeta and Andrade-Navarro, 2008
K2D3: Predict protein secondary structure content from circular dichroism spectra using theoretical spectra. Louis-Jeune et al., 2011
Marker Server: discover marker genes in sets of gene expression data. Currently you can examine a set of 80+ murine stem cell related samples. Krzyzanowski and Andrade-Navarro, 2007
BiasViz: represent amino acid bias in protein sequences from an alignment. Huska et al., 2007
StemBase: explore a database of gene expression data from stem cell samples. Porter et al., 2007
PhyloView: colour a phylogenetic tree according to taxonomy. Palidwor et al., 2006