• Feature 1
This event is organized by CBRC with financial support from the KAUST Office of Sponsored Research


​ ​

  • Day 1Monday, December 4th
  • Day 2Tuesday, December 5th
  • Day 3Wednesday, December 6th
8:00 am

Coffee & Breakfast

Building 9 - Lobby 08:00 - 08:30 Details

8:30 am


Building 9

Building 9 08:30 - 09:00 Details

9:00 am

Welcome address

Vladimir Bajic, Director Computational Bioscience Research Center, KAUST

Building 9 - Lecture hall 2 09:00 - 09:05 Details

9:05 am

Opening remarks

Mootaz Elnozahy, Dean Computer, Electrical and Mathamatical Science & Engineering Division, KAUST

Building 9 - Lecture hall 2 09:05 - 09:20 Details

Session 1: Computational Approaches and Bioinformatics in Evolutionary Biology (Chair: Robert Hoehndorf)
9:20 am

KEYNOTE LECTURE: The Impact of Admixture between Modern and Archaic Humans

The genomes of archaic and early modern humans offer a unique window into their histories. However, the sequencing and analysis of DNA from archaic humans is complicated by DNA degradation, chemical modifications and contamination. Recent technological advances have made it possible to recover nuclear DNA sequences from a number of archaic and early modern humans and a number of important insights have been obtained from the whole genome sequences that have been generated. Comparison of archaic genome sequences to the genome sequences of present-day humans has allowed us to identify sequence differences that have come to fixation or reached high frequency in modern humans since their divergence from Neandertals and Denisovans, some of which may have important functional effects in modern humans. Further, ancient genomes have provided direct evidence that interbreeding between archaic humans and early modern humans occurred and that it resulted in between 1-6% archaic human DNA in the genomes of present day non-Africans. This introgressed DNA has been shown to have both positive and negative outcomes for present-day carriers: underlying apparently adaptive phenotypes as well as influencing disease risk. I will discuss recent work in which we have identified Neandertal haplotypes that are likely of archaic origin and determined the likely functional consequences of these haplotypes using public genome, gene expression, and phenotype datasets.

Building 9 - Lecture hall 2 09:20 - 10:20 Details

Janet Kelso, Max-Planck Institute for Evolutionary Anthropology in Leipzig, Germany
10:20 am

HOCOMOCO: a Collection of Transcription Factor Binding Models for Human and Mouse Based on ChIP-seq Data and its Application in Genetics and Systems Biology

HOCOMOCO (HOmo sapiens COmprehensive MOdel Collection) is a human curated collection of position weight matrix (PWM) models for binding sites for 680 human and 453 mouse TFs. HOCOMOCO is mostly based on the ChIP-seq data, that appear to be most informative on the specificities of TF binding in vivo. We used five thousand of ChIP-Seq experiments as the raw data, the experimental datasets were taken from the GTRD database where there were uniformly processed within the BioUML framework using several ChIP-Seq peak calling tools. ChIPMunk software was used for systematic motif discovery from different peak sets. Motifs that displayed the best separation of the test (ChIP-seq peaks) and control datasets were selected. To reduce the number of irrelevant motifs emerged due to indirect binding we performed extensive computer assessment and human curation of the motifs found. As valid models, we selected those that were (i) similar to the already known motifs, (ii) consistent within a TF family, or, at least, (iii) with a clearly exhibited consensus (based on LOGO representation, manually assessed). The current version of HOCOMOCO (v.11) includes 1,302 mononucleotide and 576 dinucleotide PWMs, which describe primary binding motifs of each TF and reliable alternative binding specificities. An interactive interface and bulk downloads are available at http://hocomoco.autosome.ru and http://www.cbrc.kaust.edu.sa/hocomoco11. HOCOMOCO database can be used for exploration of different problems in genetics, medicine, and systems biology, and can support studies on evolution of TF binding sites.

Building 9 - Lecture hall 2 10:20 - 10:55 Details

Vsevolod Makeev, Institute of General Research, Russian Academy of Sciences, Moscow
10:55 am

Coffee break

Building 9 - Lobby

Building 9 - Lobby 10:55 - 11:10 Details

11:10 am

Plant Translational Research in Big Data Era

By 2050 the world's population will reach 9.1 billion, and food demand is expected to increase by 70% (FAO, 2009). To answer this “Nine billion question,” it is imperative to improve the interdisciplinary nature of crop production. In this seminar, we will discuss the use of Big Data from high-throughput phenotyping and genomics to advance our knowledge on the genetic mechanisms underlying stress adaptation in crop plants.
We performed our experiment at The Plant Accelerator®, a high-throughput phenotyping platform (HTP) that provides non-destructive quantitative measurements for plant development over time. We used HTP to phenotype rice, one of the most important cereals, under salt stress conditions. The use of HTP enabled us to obtain multiple measurements throughout time, namely plant growth and architecture, as well as water loss under control and stress conditions. The wealth of data resulting from daily measurements is a major bottleneck for further analysis. To overcome this challenge we are currently exploring new methods to analyse the collected data and to perform genetic analysis to identify genetic signatures in response to abiotic stress.

  • Sonia Negrao, KAUST

    Sonia Negrao

Building 9 - Lecture hall 2 11:10 - 11:45 Details

Sonia Negrao, KAUST
11:45 am

The Draft Genomes of Three Wild Tomato Species: Progress & Insights

The Solanum section Lycopersicon is an economically important clade that consists of 14 species including the cultivated tomato Solanum lycopersicum, which is one of the most economically important horticultural crops. Here, we sequenced the genomes of three wild tomato species: S. pimpinellifolium, S. galapagense and S. cheesmaniae.

  • Salim Bougouffa, KAUST

    Salim Bougouffa

Building 9 - Lecture hall 2 11:45 - 12:20 Details

Salim Bougouffa, KAUST
12:20 pm

Lunch break

Campus Diner

Campus Diner 12:20 - 13:30 Details

Session 2: Functional Evolution and Population Studies (Chair: Takashi Gojobori)
1:30 pm

KEYNOTE LECTURE: From Phylogeny to Phylomedicine

Nature has been the greatest experimenter on Earth for millennia. New mutations continuously arise in our genomes and their fate is determined by the action of purifying selection, genetic drift, and positive selection. Comparative sequence analysis at individual, population, and species levels yields a record of their outcomes in form of patterns of conservation and divergence of genomes. These evolutionary patterns and their underlying causes are now the foundation of many approaches to forecast adaptive and disruptive mutations found in our personal and somatic genomes. Predictive evolutionary techniques and the associated fundamental research investigations are encompassed by Phylomedicine, which is becoming a key discipline at the intersection of molecular evolution, genomics, and biomedicine. I will present highlights of our recent research in phylomedicine of Mendelian, cancer, and complex diseases.

Building 9 - Lecture hall 2 13:30 - 14:30 Details

Sudhir Kumar, Temple University, Philadelphia
2:30 pm

DeepGO: Predicting Protein Functions from Sequence and Interactions Using a Deep Ontology-aware Classifier

A large number of protein sequences are becoming available through the application of novel high-throughput sequencing technologies. Experimental functional characterization of these proteins is time-consuming and expensive, and is often only done rigorously for few selected model organisms. Computational function prediction approaches have been suggested to fill this gap. The functions of proteins are classified using the Gene Ontology (GO), which contains over 40 000 classes. Additionally, proteins have multiple functions, making function prediction a large-scale, multi-class, multi-label problem.
We have developed a novel method to predict protein function from sequence. We use deep learning to learn features from protein sequences as well as a cross-species protein–protein interaction network. Our approach specifically outputs information in the structure of the GO and utilizes the dependencies between GO classes as background information to construct a deep learning model. We evaluate our method using the standards established by the Computational Assessment of Function Annotation (CAFA) and demonstrate a significant improvement over baseline methods such as BLAST, in particular for predicting cellular locations.

  • Maxat Kulmanov, KAUST

    Maxat Kulmanov

Building 9 - Lecture hall 2 14:30 - 03:05 Details

Maxat Kulmanov, KAUST
3:05 pm

Coffee break

Building 9 - Lobby

Building 9 - Lobby 15:05 - 15:20 Details

3:20 pm

Integrative Drug Discovery Targeting Protein-Protein Interactions: The 2P2I Approach

Drug discovery is an inherently inefficient process, particularly in oncology. The difficulty in matching the immense and complex chemical world with a desired physiological effect is illustrated by limitations such as harmful side effects and drug resistance, which defy the most powerful chemotherapeutics available. Novel therapeutic targets and new ways to identify, to characterize and to develop anti-cancer drugs are needed. Inhibitors of protein-protein interaction represents an alternative and almost unexplored reservoir for drug development in oncology. In this context, our objectives are to identify, to understand, to validate and to target protein-protein interaction interfaces critically involved in tumor cell signaling, with the specific purpose of facilitating the transfer of therapeutic and pharmacological targets into preclinical and clinical development programs in oncology.
We have recently implemented an integrated drug discovery approach with an automated process combining chemoinformatics (development of a software dedicated to in silico chemical reaction and systematic energetic –docking- evaluation of the resulting chemical libraries), chemical synthesis (diversity oriented synthesis and hit explosion / Chemspeed SLTII platform) and HTS assays (pharmacological and biophysical evaluation / ECHO platform). This integrative effort will be exemplified with examples of hit(s) discovery and hit-to-lead optimization on Bromodomain or PDZ domain inhibitors development as well as a drug repurposing success of tyrosine kinase inhibitors (imatinib and masitinib).

  • Xavier Morelli, Centre National de la Recherche Scientifique

    Xavier Morelli

Building 9 - Lecture hall 2 15:20 - 15:55 Details

Xavier Morelli, Centre National de la Recherche Scientifique
3:55 pm

A Synthetic Biology Approach to Waddington Landscape and Cell Fate Determination

The process of cell fate determination has been depicted intuitively as cells travelling and resting on a rugged landscape, which has been probed by various theoretical studies. However, few studies have experimentally demonstrated how underlying gene regulatory networks shape the landscape and hence orchestrate cellular decision-making in the presence of both signal and noise. Here we tested different topologies and verified a synthetic gene circuit with mutual inhibition and auto-activations to be quadrastable, which enables direct study of quadruple cell fate determination on an engineered landscape. We show that cells indeed gravitate towards local minima and signal inductions dictate cell fates through modulating the shape of the multistable landscape. Experiments, guided by model predictions, reveal that sequential inductions generate distinct cell fates by changing landscape in sequence and hence navigating cells to different final states. This work provides a synthetic biology framework to approach cell fate determination and suggests a landscape-based explanation of fixed induction sequences for targeted differentiation.

Building 9 - Lecture hall 2 15:55 - 16:30 Details

Xiao Wang, Arizona State University
4:30 pm

Students poster session and finger buffet - Open to all - Sponsored by the KAUST Industry Collaboration Program (KICP)

Building 9

Building 9 16:30 - 19:00 Details

8:30 am

Coffee & Breakfast

Building 9 - Lobby

Building 9 - Lobby 08:30 - 09:00 Details

Session 3: Environmental Adaptation in Evolutionary Biology and Ecology (Chair: Stefan Arold)
9:00 am

KEYNOTE LECTURE: Adaptive Evolution of Vertebrate Vision

Vertebrate ancestors appeared in a uniform, shallow water environment, but modern species flourish in highly variable niches. A striking array of phenotypes exhibited by contemporary animals is assumed to have evolved by accumulating a series of selectively advantageous mutations, but the experimental test of such adaptive events has been remarkably difficult. Genetically engineering 11 ancestral rhodopsins, which regulate dim-light vision, we have shown that early ancestral rhodopsins absorbed light maximally (max) at 500 nm, from which contemporary rhodopsins with variable maxs of 480–525 nm evolved on at least 18 separate occasions. These highly environment-specific adaptations have occurred largely by amino acid replacements at 12 sites, and most of those at the remaining 191 (~94%) sites have undergone neutral evolution. The comparison between these results and those inferred by commonly-used statistical methods demonstrates that statistical tests of positive selection can be misleading without experimental support and that the molecular basis of spectral tuning in rhodopsins should be elucidated by mutagenesis analyses using ancestral pigments. In deep-sea environments, three genera of dragonfishes are unique by emitting bioluminescence with peaks at 465-485 and 500-710 nm. These fishes can discriminate small wavelength differences between 470-580 nm using rhodopsins (or RH11 pigments) and porphyropsins (RH12), which use vitamin A1 and vitamin A2, respectively, and they also discriminate wavelengths within 430-470 and 580-720 nm using “rhodopsin-like” RH21 and RH22 pigments and long wavelength-sensitive LWS1 and LWS2 pigments, respectively. Researchers have argued that dragonfishes have invented the new color vision system to visualize their new environment generated by bioluminescence, but the data show that dragonfishes have recreated the light environments of shallow water in the deep-sea by inventing blue, green, and far-red bioluminescence.

Building 9 - Lecture hall 2 09:00 - 10:00 Details

Shozo Yokoyama, Emory University, Atlanta
10:00 am

The Metaorganism Imperative - We Are not Alone

Recent years have brought a changing imperative in life sciences sparked by the revolution of genomic tools to study the molecular composition and functional organization of organisms. The development of next-generation sequencing changed our understanding of microbial diversity associated with organisms and environments. There are now a multitude of studies that support the notion that a host-specific microbiome associates with multicellular organisms and provides functions related to metabolism, immunity, and environmental adaptation, among others. Consequently, interactions and communication mechanisms of members in this metaorganism presumably play a major role in maintaining host health, microbiome stability, and resilience to environmental disturbance. This presentation will highlight and discuss recent efforts to investigate metaorganism function and evolution, and how the appreciation of host-microbe interactions provides new insight to host biology in light of the microbiome.

  • Christian R Voolstra, KAUST

    Christian R Voolstra

Building 9 - Lecture hall 2 10:00 - 10:35 Details

Christian R Voolstra, KAUST
10:35 am

Coffee break

Building 9 - Lobby

Building 9 - Lobby 10:35 - 10:50 Details

10:50 am

From Fish to Fisherman: Evolutionary Genomics of Fish and Humans in the Amazon Basin

Evolutionary genomics has been used to better understand the evolution of species and to help the development of sustainable practices of exploration of our environments.
One of such environments is the Amazon basin, which covers roughly 40% of the South American continent. In my talk, I will discuss two projects in which evolutionary genomics approaches have been used to better understand the evolutionary dynamics of fish and humans in the region. First, I will describe the genome of the pirarucu fish (Arapaima gigas), a large and widespread fish in the Amazon. Second, I will discuss the sequencing and analysis of dozens of exomes from native Amazonian people".

Building 9 - Lecture hall 2 10:50 - 11:25 Details

Sandro J. de Souza, Federal University of Rio Grande do Norte
11:25 am

Genomics-led Development of Cyanobacterial Cell Factories for Industrial Applications in Saudi Arabia

The climate, environment and industrial infrastructure of the Kingdom of Saudi Arabia (KSA) make it an ideal location for marine photosynthetic microbial cell factory (PMCF) technologies. However, to access this potential we must first develop PCMF strains capable of thriving in the harsh KSA climate. Generally, photosynthetic microbes are limited by their tolerance of light, temperature and salinity. Taken together, photosynthetic microbes from the Red Sea offer a very promising source for potential PMCF strains from which robust, highly efficient photosynthetic microbes adapted to the relevant conditions (salinity, temperature, insolation) can be developed. Here, we describe an isolation-characterization and genomic modelling pipeline targeting highly robust marine photosynthetic microbes from which PMCFs are developed by directed evolution approaches. To date we have generated over 1200 primary isolates from which a group of 120 lead strains were developed. From the latter, 44 optimized lead strains have been produced. Selected strains have been licensed for industrial applications in KSA.

  • John Archer, KAUST

    John Archer

Building 9 - Lecture hall 2 11:25 - 12:00 Details

John Archer, KAUST
12:00 pm

Group photo with the conference speakers

Follow instructions to location

Follow instructions to location 12:00 - 12:15 Details

12:15 pm

Lunch break

Campus Diner

Campus Diner 12:15 - 13:20 Details

Session 4: Biologically-inspired Computational Methods (Chair: Vladimir Bajic)
1:20 pm

KEYNOTE LECTURE: A Novel Graph-Based Constant-Column Biclustering Method for Mining Growth Phenotype Data

Growth phenotype profiling of genome-wide gene-deletion strains over stress conditions can offer a clear picture that the essentiality of genes depends on environmental conditions. Systematically identifying groups of genes from such high-throughput data that share similar patterns of conditional essentiality and dispensability under various environmental conditions can elucidate how genetic interactions of the growth phenotype are regulated in response to the environment. In this talk, I will 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. I will then propose Gracob, a novel, efficient graph-based method that casts and solves the constant-column biclustering problem as a maximal clique finding problem in a multipartite graph. We compared Gracob with a large collection of widely used biclustering methods that cover different types of algorithms designed to detect different types of biclusters. Gracob showed superior performance on finding co-fit genes over all the existing methods on both a variety of synthetic data sets with a wide range of settings, and three real growth phenotype data sets for E. coli, proteobacteria, and yeast.

Building 9 - Lecture hall 2 13:20 - 14:20 Details

Xin Gao, KAUST Computational Bioscience Research Center
2:20 pm

A Brief Review of Computational Algorithms Inspired by Nature

Optimization problems from different fields are generally difficult to solve due to the large solution space. These problems are present in our daily life and range from determining the best delivery plan for a distribution company to finding genes associated with specific diseases, where an exhaustive search would take longer than the universe has existed. Although there are several optimization algorithms, different meta-heuristics inspired by nature have been proposed to achieve improved results. These nature-based algorithms attempt to mimic the behavior of ant colonies, bees, bats, wolves, and even black holes, among others and have produced remarkably solutions for different problems. In this talk, I will present a brief overview of these nature-based algorithms and some successful applications.

Building 9 - Lecture hall 2 14:20 - 14:55 Details

Arturo Magana-Mora, National Institute of Advanced Industrial Science and Technology (AIST)
2:55 pm

Coffee break

Building 9 - Lobby

Building 9 - Lobby 14:55 - 15:10 Details

3:10 pm

Genetic Algorithms and their Application in Machine Learning

Genetic Algorithms (GAs) were invented based on the evolutionary ideas of natural selection and genetics, specially following the principles first laid down by Charles Darwin of "survival of the fittest". They were designed as adaptive heuristic search algorithm used to solve optimization problems. This talk gives an introduction of the basic concepts and terminology involved in Genetic Algorithms. Then GAs in Machine Learning will be discussed, as well as some application examples.

  • Xiangliang Zhang, KAUST

    Xiangliang Zhang

Building 9 - Lecture hall 2 15:10 - 15:45 Details

Xiangliang Zhang, KAUST
3:45 pm

Biologically-Inspired Optimization Algorithms for View Selection in OLAP

On-Line Analytical Processing (OLAP) systems provide efficient low level database support for a variety of data analysis, machine learning and knowledge extraction tasks that involve very large datasets. This talk will: (i) introduce the main concepts of OLAP, in particular the multi-dimensional data model that is relevant to machine learning, where dimensions correspond to ?features?; (ii) explain how the precomputation of various projections of the data can accelerate significantly the analysis of data; (iii) present the view selection problem that decides the set of projections to precompute in order to optimize performance under the constraints of storage and data maintenance time; and (iv) discuss how biologically inspired algorithms such as ant colony optimimization and Genetic algorithms, have been employed to solve the view selection problem.

  • Panos Kalnis, KAUST

    Panos Kalnis

Building 9 - Lecture hall 2 15:45 - 16:20 Details

Panos Kalnis, KAUST
7:00 pm

Gala Dinner - Invitation only

Yacht Club restaurant

Yacht Club restaurant 19:00 - 20:30 Details

8:45 am

Coffee & Breakfast

Building 9 - Lobby

Building 9 - Lobby 08:45 - 09:15 Details

Session 5: Spotlight on Young Talent (Chair: Xin Gao)
9:15 am

Characterization of Red Sea Cyanobacteria for Cell Factory Application in Saudi Arabia

  • Yi Mei Ng, KAUST

    Yi Mei Ng

Building 9 - Lecture hall 2 09:15 - 09:30 Details

Yi Mei Ng, KAUST
9:30 am

Functional Interrogation of Malaria metabolism reveals Species and Stages-specific Differences in Nutrient Essentiality and Drug Targeting

  • Alyaa Mohamed, KAUST

    Alyaa Mohamed

Building 9 - Lecture hall 2 09:30 - 09:45 Details

Alyaa Mohamed, KAUST
9:45 am

Genome-scale Evaluation of the Biotechnological Potential of Red Sea Derived Bacillus Strains

  • Ghofran Othoum, KAUST

Building 9 - Lecture hall 2 09:45 - 10:00 Details

Ghofran Othoum, KAUST
10:00 am

DEEPre: Sequence-based Enzyme EC Number Prediction by Deep Learning

  • Yu Li, KAUST

    Yu Li

Building 9 - Lecture hall 2 10:00 - 10:15 Details

10:15 am

Ontology Design Patterns for Combining Pathology and Anatomy: Application to Study Aging and Longevity in Inbred Mouse Strains

  • Sarah Alghamdi, KAUST

Building 9 - Lecture hall 2 10:15 - 10:30 Details

Sarah Alghamdi, KAUST
10:30 am

Coffee break

Building 9 - Lobby

Building 9 - Lobby 10:30 - 10:45 Details

10:45 am

Career Panel Discussion with Speakers, Students, Postdocs and Researchers

Moderator: Virginia Unkefer, Manager, Publication Services and Researcher Support, KAUST

Building 9 - Lecture hall 2 10:45 - 12:00 Details

12:00 pm

Lunch break

Campus Diner

Campus Diner 12:00 - 13:00 Details

Session 6: Industrial and Medical Applications (Chair: John Archer)
1:00 pm

KEYNOTE LECTURE: On Unnatural Selection: Lessons Learned from Large Scale Medical Genomics in Saudi Arabia

Natural selection is the axiom of evolutionary biology. Humans, however, can manipulate natural selection in ways that sometimes contradict it. One example is consanguineous mating, a practice that is both common and ancient in Saudi Arabia despite its clearly negative effect on reproductive fitness. The perceived societal benefits of consanguineous marriages are not sufficient to compensate for the reduced reproductive fitness and there must be compensatory biological factors perhaps the most significant of which is high fertility (a common co-variable). This long term “tug of war” has left many imprints on the Saudi genome with important medical implications. These include the conspicuous lack of the “purging effect” and the consequences of that on carrier frequency interpretation and overall Mendelian disease burden in the society. Furthermore, the characteristic signature of autozygosity presents numerous opportunities for the annotation of the human genome. In my talk, I will discuss these points in detail based on our experience with large scale medical genomics in Saudi Arabia.

Building 9 - Lecture hall 2 13:00 - 14:00 Details

Fowzan Alkuraya, King Faisal Specialist Hospital and Research Centre
2:00 pm

Methylation as a Tool for Monitoring Colon Cancer Diversity: Technical Challenges and Possibilities

It is well known that cancer populations evolve rapidly and can undergo a wide diversification. Being able to track the evolution of a cancer cell population through informative markers has enormous potential in cancer medicine.
Methylation is deeply involved in several cancers, and methylation patterns are more and more used in combination with mutational and clinical information as a tool in personalized medicine.
Using the example of a study in colon cancer this talk will illustrate the state of the art in measuring methylation levels and how that information can be used to provide accurate predictions of a wide variety of cancer subtypes.

  • Roberto Incitti, KAUST

    Roberto Incitti

Building 9 - Lecture hall 2 14:00 - 14:35 Details

Roberto Incitti, KAUST
2:35 pm

Coffee break

Building 9 - Lobby

Building 9 - Lobby 14:35 - 14:50 Details

2:50 pm

A Portable System for Rapid Bacterial Identification Using a Single-molecule DNA Sequencer and its Application to the Diagnosis of Infectious Diseases

Bacterial infection is still a serious threat to humans. Because of the great diversity of disease-causing bacteria, there is a limitation in the ability of current bacterial identification tests using bacterial culture or antibodies. DNA sequencing is more suited to identify bacterial species correctly, but the time and cost for sequencing was a problem. We thus developed a genome analyzing system for the rapid diagnosis of infectious diseases. Using a nanopore-based, single-molecule DNA sequencer, MinION, and two high-spec laptop computers, we could assemble a system that can in principle identify bacterial species in about one hour from a DNA sample of bacterial infection.
One of the key technologies here was our original database that comprehensively collected genome sequence data. The database, called GenomeSync, is one of the largest collection of complete genome sequences, containing genomes of 26,223 bacterial species (as of October 2017). Another essential technology was a software package, called GSTK, for quick and accurate identification of bacterial species for each sequencing read. This can run sequence similarity searches against the GenomeSync database on a multi-core computer, and can summarize the outputs of similarity searches based on the biological taxonomy. Furthermore, in order to get the sequencing results as quickly as possible, we installed a software for extracting sequence data from the sequencer outputs while the sequencer is running, which enabled us to analyze sequence data in a real-time manner.
Owing to the successful combination of these core technologies, we could realize the rapid and accurate analysis of bacterial composition. We hope that our system will be widely utilized for the diagnosis of infectious diseases in the future.

Building 9 - Lecture hall 2 14:50 - 15:25 Details

Tadashi Imanishi, Tokai University School of Medicine
3:25 pm

KEYNOTE LECTURE: Insights to Cardiovascular Disease Risk in Large Data Sets

UK Biobank was established to improve understanding of the causes of common diseases including CAD and recruited 502,713 (94% of self-reported European ancestry) individuals aged 40-69 between 2005 and 2010. In addition to self-reported disease outcomes as well as extensive health and life-style questionnaire data, participants are being tracked through their NHS records and national registries (including cause of deaths, hospitalisations and primary care records).
Coronary artery disease (CAD) is the commonest cause of death in the world. Large scale genetic studies in UK Biobank and other large cohorts have identified so far 100 robustly associated risk loci leading to a better understanding of disease biology. We can now start exploring the common genetic risk between CAD and the broader spectrum of cardiovascular diseases including stroke, heart failure, pulmonary artery disease, and atrial fibrillation as well as traditional risk factors.
In parallel, the Genomics England Clinical Interpretation Cardiovascular Domain is leveraging large scale whole-genome sequencing data from the 100,000 Genomes project to improve our understanding of the genetic basis of rare inherited cardiovascular disorders.

Building 9 - Lecture hall 2 15:25 - 16:25 Details

Panos Deloukas, Queen Mary University of London
4:25 pm

Closing Remarks and Announcement of Poster Competition Winners

Vladimir Bajic, Director and Takashi Gojobori, Associate Director Computational Bioscience Research Center, KAUST

Building 9 - Lecture hall 2 16:25 - 16:40 Details

7:00 pm

Dinner - Invitation only

Pure Restaurant

Pure Restaurant 19:00 - 20:30 Details