Leading Professional Society for Computational Biology and Bioinformatics
Connecting, Training, Empowering, Worldwide

Upcoming Conferences

A Global Community

  • ISCB Student Council

    dedicated to facilitating development for students and young researchers

  • Affiliated Groups

    The ISCB Affiliates program is designed to forge links between ISCB and regional non-profit membership groups, centers, institutes and networks that involve researchers from various institutions and/or organizations within a defined geographic region involved in the advancement of bioinformatics. Such groups have regular meetings either in person or online, and an organizing body in the form of a board of directors or steering committee. If you are interested in affiliating your regional membership group, center, institute or network with ISCB, please review these guidelines (.pdf) and submit your application using the online ISCB Affiliated Group Application form. Your exploratory questions to ISCB about the appropriateness of a potential future affiliation are also welcome by Diane E. Kovats, ISCB Executive Director (This email address is being protected from spambots. You need JavaScript enabled to view it.).

  • Communities of Special Interest

    topically-focused collaborative communities


  • ISCBconnect

    open dialogue and collaboration to solve problems and identify opportunities

  • ISCB Member Directory

    connect with ISCB worldwide

  • ISCB Innovation Forum

    a unique opportunity for industry

Professional Development, Training and Education

ISCBintel and Achievements

Award Winners - ISMB/ECCB 2015


Ian Lawson Van Touch Memorial Award

Outstanding Oral Poster Presentation Prize sponsored by University of California Berkeley Center for Computational Biology

F1000Research Poster Awards

RCSB PDB Poster Prize

Springer Outstanding Poster Award

Wiley Poster Prizes

Art & Science Award


Ian Lawson Van Toch Memorial Award for Outstanding Student Paper


TP025: Identification of causal genes for complex traits

Presenting Author: Farhad Hormozdiari, University of California, Los Angeles, United States

Additional authors:
Gleb Kichaev, University of California, Los Angeles, United States
Wen-Yun Yang, University of California, Los Angeles, United States
Bogdan Pasaniuc, University of California, Los Angeles, United States
Eleazar Eskin, University of California, Los Angeles, United States 


Motivation: Although genome-wide association studies (GWAS) have identified thousands of variants associated with common diseases and complex traits, only a handful of these variants are validated to be causal. We consider “causal variants” as variants which are responsible for the association signal at a locus. As opposed to association studies that benefit from linkage disequilibrium (LD), the main challenge in identifying causal variants at associated loci lies in distinguishing among the many closely correlated variants due to LD. This is particularly important for model organisms such as inbred mice, where LD extends much further than in human populations, resulting in large stretches of the genome with significantly associated variants. Furthermore, these model organisms are highly structured, and require correction for population structure to remove potential spurious associations.

Results: In this work, we propose CAVIAR-Gene, a novel method that is able to operate across large LD regions of the genome while also correcting for population structure. A key feature of our approach is that it provides as output a minimally sized set of genes that captures the genes which harbor causal variants with probability . Through extensive simulations, we demonstrate that our method not only speeds up computation, but also have an average of 10% higher recall rate compared to the existing approaches. We validate our method using a real mouse high-density lipoprotein data (HDL) and show that CAVIAR-Gene is able to identify Apoa2 (a gene known to harbor causal variants for HDL), while reducing the number of genes that need to be tested for functionality by a factor of 2.

The software is freely available for download at genetics.cs.University of California, Los Angeles.edu/caviar


Outstanding Oral Poster Presentation Prize sponsored by University of California Berkeley Center for Computational Biology


OP12: Pathway relevance ranking for tumor samples through network-based data integration

Presenting Author:  Lieven Verbeke, Ghent University / iMinds / IBCN, Belgium

Additional Authors:
Jimmy Van den Eynden, Ghent University / iMinds / IBCN, Belgium
Piet Demeester, Ghent University / iMinds / IBCN, Belgium
Kathleen Marchal, / iMinds / IBCN, Belgium
Jan Fostier, / iMinds / IBCN, Belgium


We present a new pathway relevance ranking method that is able to prioritize pathways according to the information contained in any combination of tumor related omics datasets. Key to the method is the conversion of all available data into a single network representation containing not only genes but also individual patient samples. Additionally, all data are linked through a network of previously identified molecular interactions. The performance of the new method is demonstrated by applying it to breast and ovarian cancer datasets from The Cancer Genome Atlas. By integrating gene expression, copy number, mutation and methylation data, the method’s potential to identify key pathways involved in breast cancer development shared by different molecular subtypes, is illustrated. Interestingly, certain pathways were ranked equally important for different subtypes, even when the underlying (epi)-genetic disturbances were diverse. The pathway ranking method was also able to identify subtype-specific pathways. Often the score of a pathway could only be explained by a combination of genetic and epi-genetic disturbances, stressing the need for a network-based data-integration approach. The analysis of ovarian tumors, as a function of survival-based subtypes, demonstrated the method’s ability to correctly identify key pathways, irrespective of tumor subtype. A differential analysis of survival-based subtypes revealed several pathways with higher importance for the bad-outcome patient group than for the good-outcome patient group. Many of the pathways exhibiting higher importance for the bad-outcome patient group could be related to ovarian tumor proliferation and survival.


OP14: Novel brain-specific miRNA discovery using small RNA sequencing in post-mortem human brain

Presenting Author: Christian Wake, Boston University, United States
Additional Authors:
Adam Labadorf, Boston University, United States
Alexandra Dumitriu, Boston University, United States
Andrew Hoss, Boston University, United States
Richard Myers, Boston University, United States

MicroRNAs (miRNA) are short non-coding RNAs that regulate gene expression mainly through translational repression of target mRNA molecules. More than 2700 human miRNAs have been identified and some are known to display tissue-specific patterns of expression. Here, we use high-throughput small RNA sequencing to discover novel and possibly brain-specific miRNAs in 94 human post-mortem prefrontal cortex samples from patients with Huntington's disease and Parkinson's disease and normal neuropathology. Using a custom analysis pipeline, we identified 66 novel miRNA candidates that originate in both intergenic and intragenic regions of the genome. 21 of the candidate miRNAs show sequence similarity with known mature miRNA sequences and may be novel members of known miRNA families, while the remaining 45 may constitute previously undiscovered families of miRNAs that are specific to the brain. In a small number of these novel miRNAs, preliminary differential expression analysis between neurodegenerative disease and normal samples identified differences in expression. These results suggest that a portion of these novel miRNAs may not only be unique to brain, but may have a role in the neurodegenerative disease processes.


F1000Research Poster Awards


OP15: Computationally efficient approach for novel transcript discovery across large RNA-seq dataset reveals glioblastoma-associated lncRNAs

Presenting Author:  Maria Laaksonen, BioMediTech, University of Tampere, Finland

Additional Authors:

Antti Ylipää, 1) BioMediTech, University of Tampere 2) Department of Signal Processing, Tampere University of Technology, Finland
Janne Seppälä, BioMediTech, University of Tampere , Finland
Tommi Rantapero, BioMediTech, University of Tampere , Finland
Kirsi Granberg, 1) BioMediTech, University of Tampere 2) Department of Signal Processing, Tampere University of Technology, Finland
Matti Nykter, BioMediTech, University of Tampere , Finland
Availability of RNA-sequencing data from human tumors and normal tissues has resulted in discovery of hundreds of tissue specific transcripts. Uncovering novel transcripts typically requires computationally expensive de novo transcriptome assembly and combination of assemblies across samples have proven challenging. To be able to search for new transcripts from large RNA-seq cohorts, we developed a computational approach that directly identifies unannotated genomic loci that are variably expressed within a sample set, or differentially expressed between two sample sets. These loci are then subject to gene structure analysis, allowing identification of full transcript structures in data driven manner. Our approach was validated by re-discovering a set of well annotated genes. We were able to correctly re-build known gene structures and identify the typical structural features of protein coding genes even when only a single exon of the gene was given as input.

We applied our approach to RNA-seq data of 169 primary glioblastoma samples from The Cancer Genome Atlas (TCGA). We identified 53 unannotated transcripts that did not contain good quality open reading frames, indicating that they were lncRNAs. The expression of 20 out of 22 high confidence lncRNAs was validated by PCR in at least one glioblastoma cell line. Clinical association analyses in the TCGA glioma cohort revealed that a subset of lncRNA expression profiles associates with patient survival, tumor grade and/or IDH1 mutation status. The functional analysis of lncRNA knockdowns was performed in glioblastoma cells to evaluate their significance in disease aggressiveness.
OP17: Low concordance of differential DNA methylation analysis methods 

Presenting Author:  Helen McCormick, Victor Chang Cardiac Research Institute, Australia

Additional Authors:
Eleni Giannoulatou, Victor Chang Cardiac Research Institute, Australia
Jennifer Cropley, Victor Chang Cardiac Research Institute, Australia
Catherine Suter, Victor Chang Cardiac Research Institute, Australia
DNA methylation is one of the most widely used markers for the study of epigenetic contributions to phenotypic variation and disease. There are several methods for analyzing genome-wide DNA methylation data in common use, but there has been no rigorous evaluation of their performance. We have performed a systematic assessment and comparison of four packages: MethySig, methylKit, eDMR and DSS, using an empirical dataset of 12 reduced representation bisulphite sequencing libraries (6 test, 6 control). Surprisingly, we observed very low concordance among these commonly used model-based and binomial test-based approaches: using equivalent pre-processing and filtering parameters for each method, we found that the four methods identified significant differentially methylated cytosines at a concordance rate of less than 1%. Similarly low levels of concordance were observed with identification of differentially methylated regions using tiled data. Our study highlights the need for systematic approaches to reliable differential methylation analysis via data simulation. This concept of simulation will be discussed in the context of the growing implementation of epigenomic data in human medicine.
OP19: Human paralog genes share regulatory elements and co-localize in the three-dimensional chromatin architecture
Presenting Author: Jonas Ibn-Salem, Johannes Gutenberg University, Germany
Additional Authors:
Miguel Andrade-Navarro, Faculty of Biology, Johannes Gutenberg University Mainz, Germany
Paralog genes arise from gene duplication events during evolution. The resulting sequence similarity between paralogs often leads to proteins of similar structures and functions in common pathways. Therefore it might be useful for the cell to have paralog genes co-regulated. However, since paralog genes often show also slightly different functions, for example alternative domains, it might be also useful for cells to exclusively express only one out of several paralogs for a specific function or response.
Eukaryotic genes are regulated by binding of transcription factors to distal enhancer elements which perform looping interactions to the transcription machinery at gene promoters. We hypothesised that paralog genes share common regulatory mechanism that allows co-regulation and exclusive expression.

To test this hypothesis, we integrated paralogy annotations with genome-wide data-sets of enhancer-promoter associations and genome-wide chromatin interaction data from Hi-C experiments in human cells.

With carefully sampled control data sets that take linear co-localisation of paralogs into account, we show that paralog gene pairs share a significant amount of common enhancer elements. Furthermore they are located significantly more often in the same topological association domain than expected and therefore cluster not only in the linear genome but also in the three-dimensional chromatin structure of the nucleus.

Together our results indicate that human paralog gene pairs share common regulatory mechanisms. We will further integrate expression data from different tissues and functional annotation of genes to support our findings that paralog genes tent to be expressed either collectively or exclusively depending on the cells functional needs.
OP31: Detecting small structural variants with SoftSV using soft-clipping information
Presenting Author: Christoph Bartenhagen, Institute of Medical Informatics, Germany
Additional Authors:
Martin Dugas, Institute of Medical Informatics, Germany
Numerous tools for the detection of structural variations (SVs) have been developed over the last years, including our own contribution called SoftSV. But there still remains a gap between small indels, which can be detected by gapped alignments, and large SVs (many hundred or thousand bp), which can be reconstructed by paired-end reads or read-depth information. Filling this gap remains difficult and often demands special algorithms for split-read alignments directly at the breakpoints, which only a few of the published tools do for this range of SVs.

We initially developed SoftSVs for large SVs and now expanded our approach to small and medium-sized deletions, tandem duplications and inversions (starting at 20bp). Similar to large rearrangements, we detect their exact breakpoints under the premise that no threshold filters SVs with low support or reads with low mapping quality or ambiguous mappings. Our greedy approach exploits any kind of soft-clipped alignment and reconstructs the breakpoint sequence just by comparing the soft-clipped reads at the start and end of an SV.

Using simulated and four real datasets from the 1000 Genomes Project, we evaluate the sensitivity and precision of SoftSV and four other tools. Our results show that sensitive and reliable SV detection is subject to many different factors like read length, coverage and SV type. SoftSV achieved sensitivities and PPVs between 80% and 100% consistently for all SV types on simulated datasets starting at 75bp reads and 10-15x sequence coverage, without requiring any parameter configuration by the user.

SoftSV is freely available at http://sourceforge.net/projects/softsv
OP36: Site-specific evolution of selected post-synaptic protein complexes
Presenting Author: Maciej Pajak, University of Edinburgh, United Kingdom
Additional Authors:
Martin Dugas, Institute of Medical Informatics, Germany
Clive R. Bramham, University of Bergen, Norway
T. Ian Simpson, University of Edinburgh, United Kingdom
Sequence conservation analysis of proteins belonging to the post-synaptic proteome (PSP) has previously revealed that key synaptic protein classes are present in primitive organisms preceding the emergence of nervous systems.
Recent studies suggest that evolution of the PSP may be responsible for the emergence of complex neural system function and behaviour but these analyses assess evolution only at the whole protein level.

We have developed an analysis workflow that integrates codon-resolution selection pressure estimates with domain and motif data to allow refinement of our understanding of domain-centric functionalisation of the PSP.

We show the application of this workflow to the Activity-regulated cytoskeleton protein (Arc) complex, a set of 26 Arc interacting proteins. Arc is highly conserved among placental mammals and plays a significant role in the post-synaptic density as a major regulator of long-term synaptic plasticity, the presumed molecular correlate of memory and learning.

Maximum likelihood phylogenetic inference for proteins of the Arc interactome, followed by site-by-site selection pressure analysis using a fixed effect likelihood methodology reveals a small set of positively selected sites as well as many regions under strong negative selection pressure. Mapping of these sites onto both known and predicted binding domains and post-translational modification sites allows inference of key domain-level functionalisation events during Arc complex evolution and provides a rational basis for prioritising regions for functional studies.
RCSB PDB Poster Prize


OP30: Determining the winning SH3 coalition: how cooperative game theory reveals the importance of domain residues in peptide binding

Presenting Author:  Ashley Conard, United States

Additional Authors:
Elisa Cilia, Université Libre de Bruxelles, Belgium
Tom Lenaerts, Université Libre de Bruxelles, Belgium
Cell signaling relies on protein-protein and protein-peptide interactions involving signaling domains, which typically recognize specific peptide motifs. For instance, SH3 domains bind preferably to proline-rich amino-acid motifs. Phage-display experiments allow one to determine those motifs and whether surface or core domain mutants gain or loose preference for peptide motifs. Here, we present an approach utilizing the Shapley Value (SV) from Cooperative Game Theory to determine the importance of seven residues in the Fyn SH3’s hydrophobic core. The core positions and the residues in those positions represent the players of a cooperative game in which the worth of each coalition is measured through its capacity to discriminate the binding and non-binding mutants for certain classes of peptides. The players (positions or residues) can be seen as the features of SH3 mutants in a binary classification task. Essentially, we use a feature selection method based on the SV to assign a pay-off to each core position and residue. We quantify their importance to promote peptide binding as well as their joint effects, and their interactions, represented through networks. Our results provide novel insights suggesting that the Fyn SH3 domain must contain different signatures of amino acids to promote binding to various peptide classes. This analysis highlights residue importance for proper domain function, which helps scale conservation profiles (e.g. WebLogo) by adding functionally relevant properties. These detailed pieces of information contribute an effective and novel approach to understanding the role core residues play, next to normally investigated binding-site residues, in binding specific peptides.


Springer Outstanding Poster Award


OP13: ContiBAIT: An R Package for Genome Finishing Using Strand-seq

Presenting Author:  Kieran O’Neill, British Columbia Cancer Agency, Canada


Additional Authors:
Mark Hills, British Columbia Cancer Agency, Canada
Peter Lansdorp, British Columbia Cancer Agency, Canada
Ryan Brinkman , British Columbia Cancer Agency, Canada
Strand-seq is a method for directional, low-coverage sequencing of DNA template strands in single cells. Taken together, strand-seq data from cells from the same organism provide genomic distance information. This can be used to improve the quality of early-build reference genomes made up of many contigs with no bridging sequence, firstly by grouping contigs from the same chromosome together, and secondly by ordering contigs within chromosomes. We present ContiBAIT, an R package for performing these tasks.

For grouping contigs into chromosomes, contiBAIT uses a custom clustering method based on a Chinese restaurant process. Contigs are then reoriented using a greedy algorithm which optimises for global inter-contig distance. Contig groups showing close strand similarity following reorientation are merged. 

For ordering contigs within a putative chromosome, ContiBAIT computes the strand distance between all pairs of contigs. The problem then becomes one of finding the lowest-weight Hamiltonian path over the contigs, which can be reformulated into a travelling salesman problem. ContiBAIT then finds the best ordering of contigs using the TSP package.

To validate contig clustering, we applied ContiBAIT to an early build of the mouse genome (mm2), with coordinates lifted over to mm10. ContiBAIT was able to assign most contigs with sufficient read depth for strand-seq analysis to the correct chromosome (median F-measure=0.91).

To validate contig ordering, we applied ContiBAIT to artificial contigs sampled from mm10, of sizes 1MB, 500kB and 250kB. Some chromosomes were well-ordered (Pearson's rho=0.99), while others had large sections locally well-ordered but incorrectly ordered relative to each other.


Wiley Poster Prizes


OP16: Tau Protein Related Acetylation of Histone 3 Lysine 9 in the Human Brain


Presenting Author:  Hans-Ulrich Klein, Harvard Medical School, United States


Additional Authors:

Cristin McCabe, Broad Institute, United States
Jishu Xu, Brigham and Women's Hospital and Harvard Medical School, United States
David Bennett, Rush University Medical Center, United States
Philip DeJager, Brigham and Women\'s Hospital and Harvard Medical School, United States

Accumulation of tau proteins and amyloid-ß peptides in the brain are two hallmarks of Alzheimer’s Disease (AD). Recent studies suggest that epigenetic mechanisms are likely to play a key role in the pathogenesis of AD. Here, we studied genome wide the active mark H3K9ac using ChIP-seq in 669 post-mortem human brain samples to detect alterations of the epigenome induced by tau. RNA-seq was performed for 500 samples to assess the effect on transcription. We considered modifications of local H3K9ac domains as well as large genomic regions and distinguished alterations primarily associated with tau from those with amyloid.

We identified 26,384 H3K9ac domains which primarily occurred at promoters (15,225) and enhancers (8,071). H3K9ac levels at promoters were positively correlated with transcription, even though H3K9ac alone was not sufficient for transcription. Tau protein loads were significantly associated with H3K9ac levels in 5,980 domains and had a much broader impact than amyloid (610 domains). Domains positively associated with tau showed a strong enrichment (p<10^-16) for binding sites of CTCF, which regulates chromatin structure. Indeed, we found large genomic regions showing concordant tau associated increases in H3K9ac. Average transcription in these regions was consistently up-regulated. Strikingly, effect sizes within the regions were highly correlated with the regions' proportion of open chromatin.

Our results demonstrate a genome wide change in chromatin structure in AD, which is mediated by tau. Tau is known to cause heterochromatin relaxation in Drosophila models. CTCF could be a key factor in the pathogenic process of chromatin opening.

OP18: Computational method for detecting patterns of epigenetic changes from time series ChIP-seq data
Presenting Author: Petko Fiziev, University of California, Los Angeles, United States
Additional Authors:
Jason Ernst, University of California, Los Angeles, United States

Histone modifications associate with important regulatory regions such as promoters and distal enhancers that control the expression of genes. Time-course genome-wide maps of these epigenetic marks have become available in a growing number of biological settings including stem cell reprogramming and differentiation, adipogenesis, cardiac development, circadian rhythms, embryogenesis and lymphocyte development. However, our understanding of the underlying cellular processes remains limited, because the current bioinformatics tools often fail to utilize fully the temporal aspects of this data. Here, we present a novel computational method for systematic detection of major classes of spatio-temporal patterns of epigenetic changes. The method takes as input data from a series of chromatin immunoprecipitation followed by high throughput sequencing (ChIP-seq) experiments for a single histone mark that are performed at consecutive time points during a given biological process. The method uses a probabilistic mixture model that explicitly models the spatio-temporal nature of the data to identify regions for which the mark either expands or contracts significantly with time or holds steady. Furthermore, it incorporates information about replicate experiments at each time point, which can increase the accuracy of the method. We present applications of the method on publicly available data from T-cell development, which help in understanding the underlying regulatory dynamics during this process.


Art & Science Award

A&S11 Analogue Alignment
Presenting Author: Luke Wilson, University of Dundee, United Kingdom
Additional Authors:
Jim Procter, University of Dundee, United Kingdom
Geoff Barton, University of Dundee, United Kingdom

“Multiple sequence alignments were once performed manually, and even today, we still examine automatically computed alignments to check that we can't do better.” –Jim Procter This is an image of the Jalview Abacus, a sculptural attempt to visually represent the function of the Jalview protein alignment program. The program can be used to find alignments of amino acids in similar proteins. These alignments are then used to find similarities and differences between these proteins.

This object expresses the core process of Jalview in a physical space, and plays on the relationship between high tech and low tech solutions. It is a functioning abacus built by hand from wood and steel. Each row is an extract from different similar proteins (cysteine proteases) and an alignment can be found by lining up the beads of like amino acids in the columns. If it was long enough it could be used to align the entire sequence manually.

Photography: Luke Wilson
Design and Construction: Luke Wilson in collaboration w. Jim Procter and Geoff Barton

ISCB Board of Directors


Alfonso Valencia, ISCB President, Spanish National Cancer Research Centre (CNIO), Spain
Burkhard Rost, ISCB Past President, Technical University Munich, Germany
Bonnie Berger, ISCB Vice President, MIT, United States
Terry Gaasterland, ISCB Vice President, University of California San Diego, United States
Thomas Lengauer, ISCB Vice President, Max-Planck Institute for Informatics, Germany
Christine Orengo, ISCB Vice President, University College London, United Kingdom
Reinhard Schneider, ISCB Treasurer; University of Luxembourg, Luxembourg
Scott Markel, ISCB Secretary, Dassault Systèmes BIOVIA, United States


Teresa Attwood, University of Manchester, United Kingdom
Alex Bateman, European Bioinformatics Institute, United Kingdom
Judith A. Blake, The Jackson Laboratory, United States
Alan Christoffels, University of the Western Cape, South Africa
Manuel Corpas, The Genome Analysis Centre, United Kingdom
Bruno Gaëta, The University of New South Wales, Australia
Paul Horton, AIST, Japan
Jigisha Anupama, University College Dublin, Ireland
Janet Kelso, Max Planck Institute for Evolutionary Anthropology, Germany
Richard H. Lathrop, University of California Irvine, United States
Fran Lewitter, Whitehead Institute, United States
Michal Linial, The Hebrew University of Jerusalem, Israel
Francisco Melo Ledermann, Pontificia Universidad Catolica de Chile
Jill Mesirov, The Broad Institute of MIT and Harvard, United States
Nicola Mulder, University of Cape Town, South Africa
Predrag Radivojac, Indiana University, United States
Anna Tramontano, University of Rome "La Sapienza", Italy
Olga Troyanskaya, Princeton University, United States
Lonnie Welch, Ohio University, United States
Martin Vingron, Max Planck Institute for Molecular Genetics, Germany

ECCB Committee Members


Ron Appel, Swiss Institute of Bioinformatics, Switzerland
Søren Brunak, Technical University of Denmark and University of Copenhagen, Denmark
Marie-Dominique Devignes, CNRS, University of Lorraine, Nancy, France
Jaap Heringa, Vrije Universiteit, Amsterdam, The Netherlands
Oliver Kohlbacher, University of Tübingen, Germany
Michael Linial, The Hebrew University of Jerusalem, Israel
Rodrigo Lopez, European Bioinformatics Institute, EMBL-EBI, Cambridge, United Kingdom
Yves Moreau, KU Leuven, Belgium
Marie-France Sagot, Inria Grenoble Rhône-Alpes, Lyon, France
Torsten Schwede, SIB Swiss Institute of Bioinformatics & Biozentrum, University of Basel, Switzerland
Janet Thornton, European Bioinformatics Institute, Hinxton, United Kingdom
Anna Tramontano, Sapienza University of Rome, Italy
Alfonso Valencia, Spanish National Cancer Research Centre (CNIO), Madrid, Spain
Jaak Vilo, University of Tartu, Estonia
Martin Vingron, Max Planck Institute for Molecular Genetics, Berlin, Germany

Special Talks - ISMB 2014

ST01: Nobel Prize Celebration: Arieh Warshel's Legacy - Presented by Lynn Kamerlin

Room: TBA

Date/Time:  Sunday, July 13 at 11:30 a.m. - 11:55 p.m.


 The advent of the first enzyme structures in the 1960s, coupled to increasing computer power at the time, marked a turning point for computational enzymology. Specifically, starting in 1970, a number of different QM+MM and QM/MM approaches were introduced by Warshel and coworkers to facilitate the description of reactions in enzymes. This and molecular dynamics simulations of biological reactions (that also started with Warshel’s work), as well as the development of classical force fields, mark the emergence of multiscale models for chemical reactivity, that allowed us to begin to directly translate structural information into an energetic picture, to better understand enzyme function. In my view the most effective direction to address this problem has been the Warshel’s 1980s “empirical valence bond” approach. Despite its seemingly theoretical simplicity, the empirical valence bond approach remains one of the most powerful tools to understand chemical reactivity in biological systems even today. This talk will explore the theoretical basis and historical background for this approach, and illustrate its application to a number of the most challenging problems in computational enzymology. Additionally, the unimaginable gains in computational power of recent decades have allowed for ever more complex systems to be addressed. Therefore, this talk will conclude by discussing the power of the EVB approach to address 21st Century challenges such as enzyme design, understanding protein evolution, and addressing chemical reactivity in even such big biomolecular systems as GTP hydrolysis on the ribosome.

Speaker Information

Presentation Overview
Preparing your Presentation for CCD Projectors
Speaker Ready Room
Information about the presentation computers
Presentation information for Students, Post Docs and Young Investigators!

Presentation Overview


Speakers are requested to review the conference schedules available on the conference website. Please note that minor schedule changes may continue to be made. Schedules are available at: https://www.iscb.org/cms_addon/conferences/ismbeccb2015/schedule/schedule.php

All parallel sessions are 20 minutes in length and there are three (3) per block. Speakers are asked to be available at the presentation room 10-15 minutes before the start of the first presentation.

Speakers should prepare a 15-minute presentation. The 3-5 minutes additional time will allow for movement to the podium and the opportunity to respond to one or two questions. Each room will have a presentation timer and sessions are chaired to ensure the program schedule is adhered to.


Speaker Ready Room:

Please visit the Speaker Room at least one (1) day before your presentation. A technician will be there and available to assist you to place your presentation on the main presentation computer for transfer to the computer in your presentation room.

Delegates with presentations developed on Apple computers may use their own Apple computer but are requested to meet with the technician in advance so that details can be coordinated regarding the procedure for using the Apple computer for presentations. It is recommended that Apple computer users bring their own cable adapters to connect to the presentation projectors.

The speaker room is located in Liffey Meeting Room 4 (CCD) – you can ask the volunteer staff at the Information desk for directions. It is available to conference speakers to review their conference presentations and to transfer their presentations to the meeting room they will present in.

Speakers Room Hours
Saturday July 11, Noon  – 5:00 p.m.
Sunday, July 12, 8:00 a.m. – 6:00 p.m.
Monday, July 13,  8:00 a.m. – 6:00 p.m.
Tuesday, July 14 8:00 a.m. – 6:00 p.m.  

Information about the presentation computers

Toshiba Satellite Pro R50

  • Non Reflective15.6 inch HD display
  • Latest generation of Intel Core CPUs: Celeron / Pentium / Core i3  with latest Intel HD Graphics
  • Windows 8.1
  • 500GB (5400rpm/7200rom)
  • 4GB Tiled Keyboard, Fast Gigabit LAN, ac a/g/n Wireless card,
  • 2 x USB 3.0, 1 x USB 2.0, RGB, HDMI, 0.9mp Webcam, SD Card
  • 7hr 25mins with removable Battery
  • DVD-SM or no ODD options
  • 2.3kg, 379.0(W)x258(D)x23.95(H)mm


Don't use "embedded fonts" in PowerPoint especially if there's video/audio or any other linked information in the presentation. Make sure that the Powerpoint file and video / audio-clips are put into the same folder.


Speaker Tips

Click here to download speaker tips

Attention Students, Post Docs and Young Investigators!

Please read these helpful tips on giving a quality talk at the conference.

As you prepare to give an oral presentation the following are some helpful tips for ensuring that both you and the international and interdisciplinary conference audience get the most out of your talk. As some talks will be recorded for viewing by our community for years to come, following these tips can also serve to make certain your best possible presentation serves you well in your future career.

Limit the number of slides to be presented.
A common mistake among presenters at all levels of experience is including too many slides for the allotted presentation time. We have all attended talks where the presenter either had to rush through or skip entire sections of slides due to having too many slides for the amount of time allotted to the talk. Worse is the presenter whose talk goes beyond the allotted time, and he or she ignores the session chair and/or session timer in order to give the full presentation detailed in the slides.

A rule of thumb is to have just one robust and informative slide for each minute of the presentation. Two or more slides per minute is sometimes possible, but this typically only works if half of the slides are updates to the slides shown before them, rather than completely new slides of different information. Keep in mind that an oral presentation slot has a time limit, and it will never be enough to fully explain all of your research efforts and results. The goal should be to give enough of an overview, with just enough depth, to make the audience understand your project, believe in your results, and pique their interest to follow up for further information available in your paper, on the web or in a follow up conversation with you after the talk.

ISMB/ECCB is a conference of several parallel sessions that must all start and stop at the precisely scheduled time, so if some talks go beyond the allotted time limit the entire schedule could be thrown off. With over 150 scheduled talks, one can imagine the havoc that this could create. Therefore, the ISMB schedule will be strictly adhered to by the session chairs, and presenters must be cut off if they are unable to finish their presentations on time. Please ensure you are not one of those presenters!

Prepare slides that show well from a distance.
There are two important aspects of slide preparation: Visibility and readability.

Regarding visibility, color backgrounds and text can look great on a computer screen but awful when projected, and some colors don't display well under any circumstances. Important details can fail to be projected with the wrong use of colors, so keeping colors simple and compatible is a safe bet.

Regarding readability, the devil is always in the details, and the highly data-driven aspect of computational biology can make this tip hard to follow. But, if a slide has too much data squeezed into it most audience members will not be able to see or decipher the data. If the data is important for the audience to see or follow, such a slide will serve little or no purpose.

So, this tip is intended to encourage you to consider the data included in your slides. Is it essential for the audience to be able to see it to understand it? If yes, go with simple colors and find ways to highlight and feature the most relevant data through the bold and/or color graphics such as arrows, circles, or magnified zoom options available in your presentation software.

It is also to your benefit to give your slides to the technical staff as early as possible and ask to check out how each slide displays under the actual projection display environment. This will give you time to make changes if the layout shifts using the equipment of the venue, and/or if the color washes out and needs to be changed.

Practice, practice, practice.
You can never over-rehearse an oral scientific presentation. Although slides will prompt you through each topic, it is important to practice out-loud several times. This will help you develop a suitable pace, attain a natural rhythm, and try out several options of words and phrases to find the ones that best communicate your research. It will also ensure you are able to make it through all of your slides without running out of time. If after a few run-throughs you still cannot meet the time limit, you will need to make adjustments.

Practicing is important for everyone, but it can be even more important if English is not your native language. The conference is expected to have attendees from over 50 countries. Because you will be communicating to many other non-native English speakers your pronunciation should be well exercised. If at all possible, you should ask a family member, friend, colleague from your lab or your advisor to listen to at least one practice session so you can work out the nerves of speaking to a live audience and gain valuable feedback. If possible, self-recording your presentation is another valuable tool.

Practice sessions should start well before you travel. Please make time the night before your talk to practice again. If you are scheduled to give a 20-minute talk, you should schedule one full hour of practice time that final night to allow yourself at least two or three rehearsals.

Each time you practice you will say things slightly differently, which is fine. When you give the actual conference presentation from the podium, it should sound like you have given this talk before, but not sound like you are reading from a script.

Relax and learn from your presentation experience.
Each time you give a talk you will improve your presentation skills and gain confidence in your public speaking abilities. Pay attention to what you did well and where you might have room to improve, and make a note of it for your next talk.

Whether this is the first for fifty-first time you are speaking at a major international conference, you will likely become nervous as the time of your talk approaches (even if you have given this same talk before). These nerves will likely stay with you as you start to give your talk. But, please know that almost everyone experiences this. The audience is interested in your presentation and not nearly as aware of your nerves as you are. Take a deep breath and try to slow down if needed - many speakers talk too fast when they are nervous. If you have rehearsed in advance, the nerves will subside as you hit your stride and you will do very well.

Last but not least, thank you!
There are many conference options these days, but none that are as large and internationally diverse in the field of bioinformatics/computational biology as this one. Thank you for choosing to submit your research and congratulations on having your work accepted for presentation. We hope this proves to be a positive experience, and that we will see you again at many more ISMB and ECCB conferences in the future.

Your ISMB Conference Organizers

p.s. For additional oral presentation tips, please read "Ten Simple Rules for Making Good Oral Presentations" in ISCB's official open access journal, PLoS Computational Biology, athttp://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.0030077 .

Exclusively for members

  • Member Discount

    ISCB Members enjoy discounts on conference registration (up to $150), journal subscriptions, book (25% off), and job center postings (free).

  • Why Belong

    Connecting, Collaborating, Training, the Lifeblood of Science. ISCB, the professional society for computational biology!


Supporting ISCB

Donate and Make a Difference

Giving never felt so good! Considering donating today.