Keynote Speaker

Personal Website
volkhard.helms@bioinformatik.uni-saarland.de

Biography

Volkhard Helms is a full professor at the Center for Bioinformatics, Saarland University,Germany since 2003. He did his PhD research at EMBL Heidelberg, Germany and obtained a diploma in physics from the Ludwig Maximilian University of Munich, Germany. Subsequently, he held positions at UC San Diego and the MPI for biophysics in Frankfurt, Germany. His research group in Saarbruecken works in the areas of bacterial resistance and cell fate transitions. They develop and employ computational methods ranging from molecular modeling of biomolecular interactions to data mining of genomic datasets. He has published more than 150 reviewed articles in the areas of biomolecular dynamics and interactions, structure and function of transmembrane proteins, gene-regulatory and protein interaction networks.

Title of Speech:

"Regulatory and interaction networks associated with cell fate transitions"

Abstract:
Modern high-throughput genomics and proteomics techniques allow researchers to characterizecell differentiation and disease processes at unprecedented levels of detail. For example,in normal breast cells about 130.000 interactions take place between different pairs of proteins.In matched breast cancer tissue, about 10.000 of these interactions are "rewired", because e.g.one or both interaction partners are no longer expressed or due to alternative splicing.One important task in modern bioinformatics is to identify statistically significant transitions that occur at higher frequency than expected by chance and their possible biological meanings.The talk will present our recent work on breast cancerogenesis and for different lineages ofhematopoiesis, namely the differentiation from blood stem cells into the different types of blood cells. Differentiation and diseases processes are typically regulated by so-called gene-regulatory networks formed by transcription factors, microRNAs and target genes. Our webserver TFmiR enables researchers to identify partial gene regulatory networks around a set of deregulated input genes and microRNAs and to identify statistically overrepresented 3-node and 4-node motifs in the graph. Our combinatorial algorithm DACO combines protein interaction data and domain-domain interaction data and constructs multi-protein complexes containing e.g. multiple transcription factors. In this way, data integration provides deeper biological insight into the complex regulatory machinery of cells. In summary, the talk addresses the problem of not being able "to see the forest for the trees", and how the identification of small local building blocks may aid in this. e.g. in hundreds of breast cancer patients rather than enumerating all of the differences.
Although much focus has been applied to the facet of data mining in big data, less focus has been put on the foundations of big data upon which data mining is based. These foundations include transforming raw data in a wide variety of formats and, if any, structures, to a consistent and meaningful schema upon which data mining may operate. These transformation techniques will be briefly discussed. Application of some of these techniques on an emerging source of raw data, social media, will be demonstrated

Personal website

Biography

Shao Li is a tenured professor at Tsinghua University and the deputy director of Bioinformatics Division, Tsinghua National Laboratory for Information Science and Technology. He received the MD degree from Beijing University of Chinese Medicine in 2001. From 2001, he has been devoted to the exploration of traditional Chinese medicine (TCM) from a network perspective, and the development of network pharmacology, bioinformatics, and systems biology methods. He is the founder and chairman of Specialty committee of network pharmacology, World Federation of Chinese Medicine Societies (WFCMS), and the vice chairman of Specialty committee of network pharmacology, Chinese Pharmacological Society. He has published over 100 papers, and held over 10 US and China patents. His works were highlighted by Nature China, F1000, and made the headlines in The Wall Street Journal, which was selected as one of “The World top 10 news of TCM in 2014” by WFCMS. Prof. Li won the National Outstanding Young Scientist Award (2012), Grand Challenges 2015-Young Scientists (2015), National Science & Technology Award (2004), National Education Award (2009), and National Excellent Doctoral Dissertation (2003) in China.

Title of Speech:

"Network-based TCM precision medicine"

Abstract:
Traditional Chinese Medicine (TCM) has a long history of viewing and treating an individual patient as an imbalanced system to guide the patient-tailored treatment by using numerous herbal formulae, making TCM a kind of traditional precision medicine. The holistic philosophy of TCM shares a lot with the key idea of systems biology, and also meets the requirement of overcoming complex diseases in a systematic manner. However, it is challenging to access such a holistic medicine by current reductionist “one target, one drug” approach due to the complexity nature not only in the chemical compositions of herb formula, but also in the biological systems of individual patients. To understand TCM from a systems perspective, we proposed a new approach of “network target, multi-component drug” and created a set of network target analysis algorithms to infer the association among herbs, compounds, biomolecules, phenotypes, and diseases and/or TCM syndromes. The follow-up clinical and experimental investigations demonstrated the effectiveness of our network target approach in discovering biomarkers, bioactive compounds, as well as molecular mechanisms for TCM holistic diagnosis and treatments in inflammation diseases and cancer. The results suggest that the network approach promises to be an innovative way to understand TCM, narrow the gap between Eastern and Western medical practices, and eventually achieve a systematic precision medicine.

Biography

President, Indian Society of Chemists & Biologists
Vice-chancellor, Gujarat Vidyapith, Ahmedabad, Gujarat, India.
In charge, Center of Excellence for Drug Discovery
Professor, Department of Chemistry (UGC-SAP-DSA-I and DST-FIST Supported), Saurashtra University, Rajkot - 360005 (INDIA)

Professor Anamik Shah is currently attached to a heritage and historical Gandhian University, Gujarat Vidyapith, Ahmedabad, Over and above his academic pursuits,Professor Shah has worked in diverse fields of Science & Technology, Spearheaded several scientific organizations & now sharing responsibility of few Scientific Institutes, Research Centers and more recently many rural centric Gandhian educations & extension organizations attached with Gujarat Vidyapith,Ahmedabad.

Title of Speech:

"Antitubercular heterocyclic NCEs through computer aided tools: Review of A decade long Journey"

Abstract
Tuberculosis is a global challenge across the boundaries of rich and poor nations alike due to one third population of the entire globe is infected with latent Mycobacterium tuberculosis. Increasing case of drug resistance is a big threat to the current treatment. Identification of new leads and drugs is a herculean task like finding a needle in haystack, where bioinformatics and chemoinformatics plays an important role in drug discovery research by assisting medicinal chemists in designing new molecules and its virtual evaluation. Involvement of computer aided drug design (CADD) is notable due to its great success in recent years. Also, open source platform, through which many institutes and organizations are connected, is endowed to provide affordable healthcare. Present lecture will address the efforts of our research group towards development of anti-TB agents through synthesis of focused libraries and molecular modelling. Some molecules are identified as promising leads and currently at the advanced level of screening, results of which will be discussed.

Workshops/Tutorials

Workshop on Protein Modeling, Structure-based Function Prediction & Applications

Abstract
In this workshop, participants will learn basic principles in structural bioinformatics and applications of protein modeling in structure-based function prediction, genomics (e.g. SNPs, mutation effects), and early drug discovery phase (e.g. protein-ligand binding). Participants will have a hands-on session to use free web-based programs to perform sequence analysis, secondary structure prediction and homology modeling, so that they can straight away apply these skills and knowledge in their research works without depending on installed software. In addition, we will also demonstrate how to use commercial softwares when dealing with challenging proteins. By end of this workshop, participants should be able to make own decision on protein modeling procedures, select which programs that best suit the available data, aware of the method limitations, and be able to present results in research articles.

Title of Speech:

"Identifying Functional Modules using MST-Based Weighted Gene Co-Expression Networks"