Abstract

Here we provide two similarity algo

In silico prioritization of undiscovered associations can help find causal genes of newly discovered diseases. Some existing methods are based on known associations and side information of diseases and genes. We exploit the possibility of using a neural network model, Neural Inductive Matrix Completion (NIMC) in disease-gene prediction.

Abstract

In biomedical research, ontologies are widely used to represent knowledge as well as anno

About

​We are witnessing today an enormous increase in the volume and complexity of data across a

We are now in the fourth paradigm of science: Data Science. The massive amount of structured and unstructured data has posed new challenges and opportunities to the fields of computer science and statistics. Traditional computational and statistical methods for data storage, curation, sharing, querying, updating, visualization, analysis, and privacy have been shown to fail in the big data scenario due to the unprecedented volume, velocity, variety, veracity and value of the big data. This conference will bring together a number of prominent researchers in Computer Science and Statistics with common interests and active research in big data, as well as the researchers at KAUST who regularly generate or face big data, such as those in bioscience and red sea research.

About

The life sciences have invested signif

Abstract

The success rate of new drug develo

Abstract

KAUST Assistant Professor Robert Ho

The KAUST Supercomputing Laboratory is co-organizing with NVIDIA, a leader in accelerated computing and artificial intelligence, a full-day workshop on accelerating scientific applications using GPUs on Tuesday, February 20th, 2018 in the auditorium between buildings 4 and 5. 

The age of "big data" is here: data of unprecedented sizes is becoming ubiquitous, which brings new challenges and new opportunities. With this comes the need to solve optimization problems of unprecedented sizes.

Abstract

Computational drug repurposing aims

This event is organized by CBRC with financial support from the KAUST Office of Sponsored Research

Abstract

Genome annotation is an important t

The PCCFD workshop will focus on cutting-edge research in the field of algorithmic development for CFD and multi-scale complex flow simulations.

Growth phenotype profiling of genome-wide gene-deletion strains overstresses conditions can offer a clear picture that the essentiality of genes depends on environmental conditions. In this dissertation, we first demonstrate that detecting such "co-fit" gene groups can be cast as a less well-studied problem in biclustering, i.e., constant-column biclustering. Despite significant advances in biclustering techniques, very few were designed for mining in growth phenotype data.

Abstract

Finding a maximum independent set in a graph is an NP-hard problem.

Abstract

The development of Chromatin immuno

Abstract

​​​Machine-learning (ML) techniques

Abstract

Finding a source from which high-en

Abstract

Drug discovery is a process that ta