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Gene Enrichment Profiler - Gene View

Yair Benita
Gene Enrichment or Expression View. Updated April 2017.

Blind Identification of SIMO Wiener Systems Based on Kernel Canonical Correlation Analysis

Steven Van Vaerenbergh
We consider the problem of blind identification and equalization of single-input multiple-output (SIMO) nonlinear channels. Specifically, the nonlinear model consists of multiple single-channel Wiener systems that are excited by a common input signal. The proposed approach is based on a well-known blind identification technique for linear SIMO systems. By transforming the output signals into a reproducing kernel Hilbert space (RKHS), a linear identification problem is obtained, which we propose to solve through an iterative procedure...

Unscented Kalman Filter (UKF) applied to FitzHugh-Nagumo neuron dynamics

Henning U. Voss
Unscented Kalman Filter (UKF) applied to FitzHugh-Nagumo neuron dynamics. Voltage observed, currents and inputs estimated. FitzHughNagumo() is the main function that calls the other functions. A detailed description is provided in H.U. Voss, J. Timmer & J. Kurths, Nonlinear dynamical system identification from uncertain and indirect measurements, Int. J. Bifurcation and Chaos 14, 1905-1933 (2004). I will be happy to email this paper on request. It contains a tutorial about the estimation of hidden states...

Reanalysis of mouse ENCODE comparative gene expression data

The Mouse ENCODE Consortium reported that comparative gene expression data from human and mouse tend to cluster more by species rather than by tissue. This observation was surprising, as it contradicted much of the comparative gene regulatory data collected previously, as well as the common notion that major developmental pathways are highly conserved across a wide range of species, in particular across mammals. Here we show that the Mouse ENCODE gene expression data were collected...


This script uses the PharmacoGx package to download the 2013 version of the Genomics of Drug Sensitivity in Cancer (GDSC) and Cancer Cell Line Encyclopedia (CCLE) datasets (Haibe-Kains et al, Nature 2013). It provides an example on how to compare biological replicates done at different sites (AZD6482 and Camptothecin within the GDSC project), and drugs profiled both in GDSC and CCLE. It also contains code computing Pearson correlation for gene expressions, copy number variations (CNV)...

R script and data for: A research note regarding "Variation in cancer risk among tissues can be explained by the number of stem cell divisions"

Tomasetti and Vogelstein argued that 2/3 of human cancers are due to ‘bad luck’ and that “primary prevention measures [against cancer] are not likely to be very effective”. We demonstrate that their calculations for hepatocellular carcinomas overlooked a major subset of these cancers proven to be preventable through vaccination. The problem, which is not limited to hepatocellular carcinoma, arises from the general reliance of their analysis on average incidences in the United States and the...

UQP heuristic methods

Shankarachary Ragi
Here, several heuristic methods to solve UQP are included: domeig.m contains the dominant eigenvector matching heuristic greedy.m contains the greedy strategy rswapgreedy.m contains the row-swap greedy strategy sdprel.m contains the semidefinite relaxation method pwr.m contains the power method sim_run.m is the main file, which calls each of the above methods and compares the performance.

Identification of mislabelled samples using gene-based gender identification

Lilah Toker
This is the code and the data required to reproduce the results of our analysis reported in the manuscript "Whose sample is it anyway? Widespread misannotation of samples in transcriptomics studies"

Feature Selection Based on High Dimensional Model Representation

Gulsen Taskin
This project provides the implementation of the algorithm proposed in the article "Feature Selection Based on High Dimensional Model Representation for Hyperspectral Images" (DOI:10.1109/TIP.2017.2687128). The project also contains the implementations of the other feature selection algorithms used in the article. In order to give the users the ability to recreate the results in article, the datasets and a couple of visualisation scripts are also provided. By running the algorithm, you will use eight different feature...

LOWESS analysis for visualization of GEDDs

Long H. Do
In our published finding (Do et al. 2015), we find evidence against domains of genome-wide gene dysregulation (GEDDs) in the Down syndrome mouse model and DS human iPSCs as compared to original findings from Letourneau et al. 2014. We have supplied the following script to allow other investigators to quickly visualize and compare their RNAseq gene expression datasets to search for corresponding GEDDs. The script performs a locally weighted scatterplot smoothing (LOWESS) analysis of RNAseq...

Plot Dose Response Curve

Yair Benita
Fitting of dose-response curve for single agent data

Rolling Decolorization Based on KL Divergence

Yule Yuan
We present, for the first time, a decolorization algorithm of maximizing the image content diversity via KL divergence.

Piecewise Histogram Equalization

Jose-Luis Lisani
This code implements a simple contrast enhancement algorithm based on histogram equalization (HE). The proposed algorithm performs a piecewise affine transform of the intensity levels of a digital image such that the new cumulative distribution function will be approximately uniform (as with HE), but where the stretching of the range is locally controlled to avoid brutal noise enhancement. We call this algorithm Piecewise Affine Equalization (PAE). The code, algorithm description and an online demo were...

Adaptive Surround Modulation

Arash Akbarinia
In this article we have addressed the problem of colour constancy through a biologically-inspired centre-surround modulation. In our dynamic algorithm we account for the contrast variability of receptive fields typical of our visual cortex.

Simple Numerical Analysis of the Multi-looked Interferometric Phase Error for K-distributed signals

Paco Lopez Dekker
A simple numerical simulation to evaluate the multi-looked interferometric phase error for K-distributed speckle and compare it with the typical case of circular-Gaussian homogeneous speckle. Since the amplitude distribution has a longer tail, the (confirmed) expectation is that the phase uncertainty increases (dominant scatterers reduce the effective number of looks)

RTRMC - Low-rank matrix completion via preconditioned optimization on the Grassmann manifold

Nicolas Boumal
RTRMC is an algorithm to solve the low-rank matrix completion problem. This is notably useful in recommender systems (for example, to recommend movies to people based on movies they have rated in the past and based on the ratings obtained from other users as well.) The algorithm runs Manopt (a toolbox for optimization on Riemannian manifolds) on a non-convex formulation of the low-rank matrix completion problem on the Grassmann manifold.

Non-Local Means Operators via Low-Rank Approximation

Nir Sharon
We present a method for improving a non-local means (NLM) operator by computing its low-rank approximation. The low-rank operator is constructed by applying a filter to the spectrum of the original NLM operator. This results in an operator, which is less sensitive to noise while preserving important properties of the original operator. The method is efficiently implemented based on Chebyshev polynomials and is demonstrated on the application of natural images denoising. For this application, we...

A q-Quantile Estimator for High-Dimensional Distributions

Assaf Glazer
In this paper we introduce a novel method that can efficiently estimate a family of hierarchical dense sets in high-dimensional distributions. Our method can be regarded as a natural extension of the one-class SVM (OCSVM) algorithm that finds multiple parallel separating hyperplanes in a reproducing kernel Hilbert space. We call our method q-OCSVM, as it can be used to estimate q quantiles of a highdimensional distribution. For this purpose, we introduce a new global convex...

MAPS: Optimized GPU and Multi-GPU Programming Framework

Tal Ben-Nun
MAPS (Memory Access Pattern Specification) is an open-source, header-only C++ CUDA template library for automatic multi-GPU programming and optimization of GPU kernels, implementing the Memory-Oriented Programming model. The framework leverages memory access patterns to provide near-optimal performance on various architectures. Using MAPS: - Automatically produces optimized GPU code - Separates complex indexing and shared memory optimizations from the algorithm - Transparently manages multi-GPU memory segmentation and inter-GPU communication - Provides familiar STL-based interfaces (containers and...


Yoav Benjamini
The use of big data is becoming a central way of discovering knowledge in modern science. Large amounts of potential findings are screened to discover the few real ones. To verify these discoveries a follow-up study is often conducted, wherein only the promising discoveries are followed up. Such follow-up studies are common in genomics, in proteomics, and in other areas where high-throughput methods are used. We show how to decide whether promising findings from the...

Multiscale Anomaly Detection Using Diffusion Maps

Gal Mishne
We propose a multiscale approach to anomaly detection in images, combining spectral dimensionality reduction and a nearest-neighbor-based anomaly score. We use diffusion maps to embed the data in a low dimensional representation, which separates the anomaly from the background. The diffusion distance between points is then used to estimate the local density of each pixel in the new embedding. The diffusion map is constructed based on a subset of samples from the image and then...

Extracting Diurnal Patterns of Real World Activity from Social Media

Nir Grinberg
In this study, we develop methods to identify verbal expressions in social media streams that refer to real-world activities. Using aggregate daily patterns of Foursquare checkins, our methods extract similar patterns from Twitter, extending the amount of available content while preserving high relevance. We devise and test several methods to extract such content, using timeseries and semantic similarity. Evaluating on key activity categories available from Foursquare (coffee, food, shopping and nightlife), we show that our...

DRAMSim2 - A cycle accurate DRAM simulator modified for row-buffer caching

Dave Wilkinson
Reproducibility experimentation for "A permutation-based page interleaving scheme to reduce row-buffer conflicts and exploit data locality" that uses a modified DRAMSim2 to simulate SPEC CPU benchmarks with an interleaved row-buffer addressing scheme.

Audio Visual Voice Activity Detection Using Diffusion Maps

David Dov
Abstract—The performance of traditional voice activity detectors significantly deteriorates in the presence of highly nonstationary noise and transient interferences. One solution is to incorporate a video signal which is invariant to the acoustic environment. Although several voice activity detectors based on the video signal were recently presented, merely few detectors which are based on both the audio and the video signals exist in the literature to date. In this paper, we present an audio-visual voice...

Multi-Scale Patch-Based Image Restoration - Denoising

Michael Elad
Many image restoration algorithms in recent years are based on patch-processing. The core idea is to ecompose the target image into fully overlapping patches, restore each of them separately, and then merge the results by a plain averaging. This concept has been demonstrated to be highly effective, leading often times to state-of-the-art results in denoising, inpainting, deblurring, segmentation, and other applications. While the above is indeed effective, this approach has one major flaw: the prior...

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