2018 Webinars

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2018 was very productive in terms of the webinars. In total, we had 8 webinars. We have opened our youtube channel to reach more people. You can find our webinar videos both from our bigmarker and youtube channels.

Also we initiated a collaborative effort with RSG Colombia and started to work together. Have a look at their youtube channel!

January 2018

  • Title: Integrative Modeling of Biomolecular Complexes
  • Presenter: Assoc. Prof. Ezgi Karaca from Dokuz Eylül University
  • Date: January 31, 2018
  • Language: English
  • Abstract: Life is operated at the nanometer scale through orchestrated communications of biomolecules. By dissecting this nanoworld, we can acquire a fundamental understanding of how biological macromolecules function, how they are related to disease-linked pathways and how to design drugs targeting them. This understanding led to the birth and rise of Structural Biology, the study of the structures of biomolecules and their complexes at atomic resolution. In this webinar, Dr. Karaca will briefly introduce the basic Structural Biology techniques and the data types acquired with them. This will be followed by a comprehensive explanation of how to incorporate Structural Biology data into biomolecular simulations, especially into docking. Finally, she will talk about her latest research on integrative modeling, recently published in Nature Methods. For more, please see: https://goo.gl/EdUvBq
  • Bigmarker: https://www.bigmarker.com/bioinfonet/EzgiKaraca
  • Youtube: https://www.youtube.com/watch?v=jmFxZDTmEBo

April 2018

  • Title: An evolutionary genomic framework for tackling problems in conservation and biodiversity.
  • Presenter: Asst. Prof. İsmail K. Sağlam from Hacettepe University
  • Date: April 16, 2018
  • Language: English
  • Abstract: Today, the fıeld of conservation biology has risen to the forefront of scientific endeavors as only with a successful translation of conservation science to conservation practices can we hope to combat threats to the sustainability and well being of our ecosystems. As in all fields of the biological sciences the genomic revolution has the potential to rapidly change how we understand and approach conservation studies. The impact of this revolution has been most felt in the applied fields of medical and agricultural sciences. This has resulted in great advances in these fields as well as ever more refined methods for analyzing genomic data. However, the utilization of genomic data in the third major applied field of biology, conservation and environmental studies, is still in its infancy. Currently, genomic methods for conservation biology revolve mostly around describing spatial patterns of genomic differentiation and very little attention has been given to developing new methods that can utilize the vast amount of information available in the genome. One key insight which can be obtained from genome wide data for conservation biology is how the genomic basis of adaptation can directly inform conservation policy. In this talk, I will concentrate on three examples which show how understanding genomic patterns of speciation, evolutionary history and life history evolution can help us solve real life problems in biodiversity and reshape ongoing conservation policies. I will also detail how this approach can be useful in understanding the complex adaptations taking place in organism that are increasingly forced to live under human dominated landscapes. This framework, which merges adaptation genomics with conservation biology, emphasizes the importance of structuring conservation efforts around key adaptive units that strengthen species survival under changing conditions and demonstrates the potential of evolutionary genomics in informing conservation strategies facilitating the preservation of keystone species and ecosystems.
  • Bigmarker: https://www.bigmarker.com/bioinfonet/IsmailKSaglam
  • Youtube: https://www.youtube.com/watch?v=PzRpvKu8GMk

June 2018

  • Title: Beyin Metabolizması Genom Ölçeğinde Modellenmesi (Genome-scale brain metabolic networks as scaffolds for mapping disease-related alterations)
  • Presenter:  Assoc. Prof. Tunahan Çakır from Gebze Technical University
  • Date:  June 11, 2018
  • Language: Turkish
  • Abstract: Integrative systems-wide analysis of data and networks at genome-scale enables a holistic understanding of the functionality and working principles of the cell. Metabolic networks are among major cellular network types since it is the metabolism that runs the cellular factory. Therefore, reconstruction of brain-specific metabolic networks is crucial to map the effect of brain-related diseases such as neurodegenerative diseases and brain tumors on cell metabolism. In this talk, I will focus on our efforts on reconstructing brain-specific metabolic networks that take into account neuron-astrocyte specificity and the interactions between these two essential cell types. Then, I will present the use of the reconstructed networks as scaffolds to map transcriptome data for neurodegenerative diseases using a graph-based approach termed reporter pathways. I will also present our work on constraint-based modelling of brain metabolic networks for the analysis of brain tumors. A key point in modelling some neurodegenerative diseases such as Alzheimer’s Disease and Parkinson’s Disease is to take into account the aggregation of disease specific proteins in the cell. I will conclude with our ongoing research on Parkinson’s Disease where we map transcriptome data on the reconstructed brain-specific metabolic networks to demonstrate the effect of alpha-synuclein aggregation on brain metabolism.
  • Bigmarker: https://www.bigmarker.com/bioinfonet/TunahanCakir
  • Youtube: https://www.youtube.com/watch?v=z8MV-eu65zI

July 2018

  • Title: Tümörlerdeki Ardışık Kısa Tekrar Dizileri ve Immünoterapi
  • Presenter: Dr. Tuğçe Bilgin Sonay from  University of Lausanne
  • Date: June 12, 2018
  • Language: Turkish
  • Abstract: Hastalıklara sebep olabilecek fenotipik çeşitliliğin kaynakları günümüzün en önemli araştırma konularının başında geliyor. DNA’daki tek nükleotit değişimleri, ve daha büyük yapısal değişimlerinin yanı sıra kopya sayısı mutasyonları da gelişen dizileme teknolojileri sayesinde daha detaylı araştırılmaya başlandı. Özellikle ardışık kısa tekrar dizilerindeki kopya sayısı değişimleri, tüm genomik mutasyonlar arasında en yüksek hıza sahip olmaları ve sebep oldukları fenotipik değişimin derecesel ve geri dönüşümlü olması sebebiyle son yıllarda oldukça önem kazandılar. Bu tekrar dizileri sadece insandan insana değişmez, tek bir insanda bile farklı kopya sayılarında bulunabilirler. Gen bölgelerinde kopya sayısını değiştiren tekrarlar Huntington, ataksiya gibi hastalıklara sebep olmalarıyla bilinirler. DNA tamir sisteminin işlememesi durumunda tümörlerde çokca bulunan bu mutasyonları anlamak hem kanser oluşumunu anlamamıza yardımcı oluyor hem de bu tümörler için immünoterapilerin geliştirilmesine öncülük eden bir role sahiptirler.
  • Bigmarker: https://www.bigmarker.com/bioinfonet/TugceBilgin
  • Youtube: https://www.youtube.com/watch?v=GmjwyTZinjU

August 2018

  • Title: Computational Analysis and Integration of Large-Scale Biological Data with Deep Learning Approaches
  • Presenter: Dr. Tunca Doğan from EMBI – EBI & METU
  • Date: August 2, 2018
  • Language: English
  • Abstract: Machine learning and data mining techniques are frequently employed to make sense of large-scale and noisy biological/biomedical data accumulated in public servers. A key subject in this endeavour is the prediction of the properties of proteins such as their functions and interactions. Recently, deep learning (DL) based methods have outperformed the conventional machine learning algorithms in the fields of computer vision, natural language processing and artificial intelligence; which brought attention to their application to the biological data. In this talk, I’m going to explain the DL-based probabilistic computational methods we have recently developed in our research center (KanSiL, Graduate School of Informatics, ODTU); first, to predict the functions of the uncharacterised proteins (i.e., DEEPred); and second, to identify novel interacting drug candidate molecules for all potential targets in the human proteome (i.e., DEEPscreen) to serve the purposes of drug discovery and repositioning, together with the aim of biomedical data integration. Apart from the benefits of employing novel DL approaches, I’ll also mention the limitations of DL-based techniques when applied on the biological data, to explain why deep learning alone cannot solve every problem related to bioinformatics.
  • Bigmarker: https://www.bigmarker.com/bioinfonet/TuncaDogan
  • Youtube: https://www.youtube.com/watch?v=ijr0B5oTnuY

October 2018

  • Title: The FoundationOne® Assay for Genomic Profiling of Solid Tumor Cancers
  • Presenter: Dr. Abdullah Karaman from  University Hospital Zurich
  • Date: October 5, 2018
  • Language: English
  • Abstract: Comprehensive genomic tumor profiling is the basis of precision medicine in the modern era of cancer diagnosis and treatment. The possibility to profile cancer genomes and identify driver mutations in individual tumors has changed the way how oncologists diagnose cancer, decide on therapies and identify patients for clinical trials. At the University Hospital Zurich and in in collaboration with Roche, Switzerland and Foundation Medicine Inc., Cambridge, USA, we have established the validated diagnostic FoundationOne® assay for solid tumors. The FoundationOne® assay is designed to detect various genomic alterations in 315 cancer related genes including single nucleotide variants, indels and copy number alterations. In addition, fusions and rearrangement events in 28 cancer associated genes are assessed. Besides these alterations, the microsatellite status (MSI) of 114 intronic homopolymer repeat loci and the tumor mutational burden (TMB) is determined as biomarkers for immun-checkpoint inhibitors. For its application in the clinical practice, the assay was designed to work with common FFPE blocks while guaranteeing a specificity of ≥ 99% and sensitivity of 90-99%. To reliably identify driver mutations in highly heterogeneous cancer samples, the assay includes targeted resequencing of exons with a median coverage of 500x. The FoundationOne® has already established itself as an essential element at tumor board meetings, where it supports oncologists in the diagnosis and decision making process for succeeding treatment options. Here, I will introduce the audience to the assay, give an overview of the first results obtained at the UniversityHopsital Zurich, will demonstrate its advantages and give statistics on its performance.
  • Bigmarker: https://www.bigmarker.com/bioinfonet/AbdullahKahraman
  • Youtube: https://www.youtube.com/watch?v=zB5PjaGbrUA

October 2018

  • Title: Cancer Biomarkers Using Integrative Single Cell and Bulk Sequencing
  • Presenter: Akdeş Sevim Harmancı from
  • Date: October 23, 2018
  • Language: English
  • Abstract: Cancer is a disease of genomic and epigenomic alterations. Single nucleotide changes, copy number variations (CNV), chromosomal rearrangements and modification in DNA methylation together drive the formation of a tumor. The integrative ‘omic’ approaches in cancer research have led to a deeper understanding of tumor biology and are establishing the foundation necessary to support the long-term goals of personalized medicine. In this talk, I will talk about identifying brain tumor biomarkers using integrative bulk or single-cell sequencing data. This talk will consist of two parts. The first part will cover our work where we characterized non-NF2 meningiomas through complex integrative analysis of genetic and epigenetic data. I will also explain the epigenetic and genetic mechanisms leading to atypical meningioma and malignant glioma transformation. The second part will introduce our algorithm named CaSpER, that identifies visualizes and integrates CNV events in multiscale resolution using single-cell and bulk RNA-Sequencing data.
  • Bigmarker: https://www.bigmarker.com/bioinfonet/AkdesSerinHarmanci
  • Youtube: https://www.youtube.com/watch?v=FSL3KT8gY2s

December 2018

  • Title: What ancient and modern DNA tells us about our human past?
  • Presenter: Dr. Stephan Schiffels from Max Planck Institute for the Science of Human History
  • Date: December 12, 2018
  • Language: English
  • Abstract: Our human past leaves traces in our genomes, via population size changes, admixture events and migration patterns. Via genetic analyses, we can therefore read human history from our genomes, which adds critically to our growing body of pre-historical evidence from archaeology and linguistics. In this talk, I will introduce the field of historical population genetics, and showcase three examples: First, I will show how our genomes contain information about the origins of our species in Africa, in the deep past. Second, I will demonstrate how we can use ancient DNA from Anglo-Saxon remains in Great Britain to investigate the nature and consequences of the Anglo-Saxon migration period. Third, I will introduce our most recent project, in which we use ancient and modern DNA to investigate the peopling of North America.
  • Bigmarker: https://www.bigmarker.com/bioinfonet/What-ancient-and-modern-DNA-tells-us-about-our-human-past
  • Youtube: Will be available soon

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