Creating is Understanding: Synthetic Biology Masters Complexity – Best Poster Awards

The recent EMBO Workshop: Creating is Understanding: Synthetic Biology Masters Complexity (22 – 25 Sep) covered various themes that are geared toward basic research while being at the forefront of synthetic biology.

110 researchers came together at the EMBL Advanced Training Centre in Heidelberg, Germany for 3,5 days of talks, posters and networking. Here we present the work of 4 scientists who received best poster awards at the conference by popular vote.

Engineering portability of the CcaSR light switch for the control of biofilm formation in Pseudomonas putida

Angeles Hueso-Gil is a PhD researcher at the Spanish National Centre for Biotechnology in Madrid.

Authors: Angeles Hueso-Gil (1), Ákos Nyerges (2), Csaba Pál (2), Belén Calles (1), Victor de Lorenzo (1)

Two of the technical challenges faced by contemporary microbiology involve controlling gene expression using light and regulating bacterial biofilm formation, determined by the intracellular levels of the secondary messenger c-di-GMP. CcaSR system is one of the light switches repeatedly used for transcription induction in Escherichia coli. This two-component system represented a good candidate for its adaptation to Pseudomonas putida. Previous attempts have tried to use this microorganism as chassis for the implementation of new pathways, being biofilm formation an important function to control. To this end, we unified CcaSR components in one single construct and randomly mutagenized their regulatory regions to find a clone with a balanced expression of the system key parts inside P. putida. The combination of this novel mutagenization process with a proper screening, which included a first sorting of the libraries and the later isolation of colonies, lead us to a clone with a much improved induction by green light. The selected variant had a notable capacity in response to green light. Finally, optimized CcaSR was used to control the expression of super-efficient variant of PleD, a diguanylate cyclase of Caulobacter which allowed a tight control of c-di-GMP levels, and therefore, of biofilm production.

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(1) National Centre for Biotechnology, Spain
(2) Biological Research Centre of the Hungarian Academy of Sciences, Hungary

Designer membraneless organelles enable orthogonal translation in eukaryotes

Christopher Reinkemeier is a PhD student at EMBL Heidelberg, JGU Mainz and IMB Mainz, Germany

Christopher Reinkemeier (1,2,3), Gemma Estrada Girona (3), Edward A. Lemke (1,2,3)

Genetic code expansion is a powerful tool to study and control protein function with single-residue precision. It is widely used to e.g. perform labeling for microscopy or to photocontrol proteins. This is achieved by introducing an orthogonal tRNA/synthetase suppressor pair into the host, to recode a stop codon to incorporate a noncanonical amino acid (ncAA) into the nascent chain. This technique is codon-specific, but it cannot select specific mRNAs, so naturally occurring stop codons could be suppressed leading to potential interference with housekeeping translation. Nature avoids cross-talk between cellular processes by confining specific functions into organelles. We aimed to design an organelle dedicated to protein engineering, but as translation is a complex process requiring hundreds of factors to work together, membrane-encapsulation would not be feasible. Inspired by the concept of phase separation we hypothesized that such an organelle could instead be designed membraneless. Phase separation can generate high local concentrations of proteins and RNAs in cells and has recently gained attention owing to its role in the formation of specialized organelles such as nucleoli or stress granules. Despite being membraneless and constantly exchanging with the cytoplasm/nucleoplasm, these organelles still perform complex tasks, such as transcription. We combined phase separating proteins with microtubule motor proteins to generated orthogonally translating organelles in living cells that contain an RNA-targeting system, the stop codon suppression machinery and ribosomes. These large organelles enable site- and mRNA-specific ncAA incorporation, decoding one specific codon exclusively in the mRNA of choice. Our results demonstrate a simple yet effective approach to the generation of semi-synthetic eukaryotic cells containing artificial organelles to harbor two
distinct genetic codes, providing a route towards customized orthogonal translation and protein engineering.

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(1) Johannes Gutenberg University Mainz, Germany
(2) Institute of Molecular Biology, Germany
(3) EMBL Heidelberg, Germany

Metabolic perceptrons for neural computing in biological systems

Paul Soudier is a PhD Student at the French National Institute of Agricultural Research, France

Amir Pandi (1), Mathilde Koch (1), Peter Voyvodic (2), Paul Soudier (1), Jerome Bonnet (2), Manish Kushwaha (1), Jean-Loup Faulon(1)

Synthetic biological circuits are promising tools for developing sophisticated systems for medical, industrial, and environmental applications. So far, circuit implementations commonly rely on gene expression regulation for information processing using digital logic. Here, we present a new approach for biological computation through metabolic circuits designed by computer-aided tools, implemented in both whole-cell and cell-free systems. We first combine metabolic transducers to build an analog adder, a device that sums up the concentrations of multiple input metabolites. Next, we build a weighted adder where the contributions of the different metabolites to the sum can be adjusted. Using a computational model fitted on experimental data, we finally implement two four-input of metabolite combinations by applying model-predicted weights to the metabolic perceptron. The perceptron-mediated neural computing introduced here lays the groundwork for more advanced metabolic circuits for rapid and scalable multiplex sensing.

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(1) French National Institute of Agricultural Research, France
(2) INSERM, France

Programmed uptake of biomacromolecules into protocells

Wiggert Altenburg is a PhD student at the Eindhoven University of Technology, The Netherlands

Wiggert Altenburg, Amy Yewdall, Daan Vervoort, Alex Mason, Jan van Hest

The bottom up recreation of cellular processes into synthetic compartments has, in recent years, emerged as an exciting line of research with which to study biological processes in a controlled environment. However, the interior of a living cell is a difficult milieu to mimic in bottom-up synthetic cells, as it is an environment crowded with high concentrations of many different biomacromolecules. In this work, we describe the development of a powerful new tool to more accurately emulate the cell cytosol in discrete coacervate-based protocells. The coacervate core utilized herein not only provides an inherently crowded and highly charged microenvironment, but has also been chemically modified to interact specifically with recombinantly expressed proteins. Our method leverages the well-established binding of His-tagged proteins to Ni2+-nitrilotriacetic acid, which ensures that macromolecules are taken up in a highly efficient, yet gentle manner, thus preserving biological activity. The straightforward method allowed for both control over the amount taken up and an increased local concentration. Moreover, the engineered uptake of proteins was then employed to study two key aspects: the effect of the Ni-NTA interaction on the diffusivity of incorporated proteins, and the enhancement in activity of an encapsulated two-enzyme cascade. This direct and targeted method of protein uptake into a discrete, membrane bound platform is a significant step forward for synthetic cells, and will enable the engineering of highly complex enzyme and signaling networks with increasingly life-like properties.

Poster currently not available

Eindhoven University of Technology, The Netherlands

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New EMBL Course and Conference postcards

We know how much our course and conference participants love the postcards at the registration desk, so we have created a new batch. These will be available from October on for you to take as a souvenir or send to your loved ones. EMBL offers a postal service on-site, so you can even send them right on that day!

A pop-art vision of yeast cells. Design by Petra Riedinger

EMBO Conference Series: Protein Synthesis and Translational Control; Graphics: Petra Riedinger · Image: Marietta Schupp
EMBO Workshop: Imaging Mouse Development; Image: Manuel Eguren/EMBL
EMBO Workshop: Integrating Systems Biology: From Networks to Mechanisms to Models; Graphics: Beata Science Art
EMBL Conference: The Human Microbiome; Graphics: Petra Riedinger
EMBO Conference: Quantitative Principles in Biology; Graphics: EMBL Design Team
EMBO | EMBL Symposium: Organoids: Modelling Organ Development and Disease in 3D Culture; Graphics: Beata Science Art
EMBO | EMBL Symposium: Systems Genetics: From Genomes to Complex Traits; Graphics: EMBO Design Team
EMBO | EMBL Symposium: The Four-Dimensional Genome; Graphics: EMBO Design Team
EMBO | EMBL Symposium: Quality Control – From Molecules to Organelles; Graphics: EMBO Design Team
EMBO Conference Series: Protein Synthesis and Translational Control; Graphics: Petra Riedinger · Image: Marietta Schupp
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Multiomics to Mechanisms Symposium – Best Poster Awards

The recent EMBO|EMBL Symposium: Multiomics to Mechanisms – Challenges in Data Integration (11-13 Sep 2019) addressed ways of integrating large-scale biological data across the different omics fields.

258 researchers from various fields gathered in Heidelberg last week to listen to 36 talks and engage with 146 poster presenters. Here we present the posters of 5 scientists who received best poster awards at the conference by popular vote.

Benchmarking of multi-omics joint  dimensionality reduction (DR) approaches for cancer study

Laura Cantini is a CNRS Research Scientist at IBENS in France.

Authors: Laura Cantini (1), Pooya Zakeri (2), Aurelien Naldi (1), Denis Thieffry (1), Elisabeth Remy (3), Anaïs Baudot (2)

Dimensionality Reduction (DR), decomposing data into low-dimensional spaces while preserving most of their information content, is among the most prevalent machine learning techniques in data mining. With the advent of high-throughput technologies, high-dimensional data have become a standard in biology, emphasizing the use of DR. This phenomenon is particularly pronounced in cancer biology, where consortia have profiled thousands of patients for multiple molecular assays (“multi-omics”), including at the emerging single-cell scale. DR approaches have been mainly applied to single omics data leading to cancer subtyping, tumor sub-clones quantification and immune infiltration quantification. Recently, DR approaches designed to jointly analyze multiple omics have been proposed. Integrative DR methods are based on various mathematical assumptions, ranging from extensions of CCA, tensors, or more general data fusion approaches, which makes difficult to chose which method to apply.
In this context, we here in-depth benchmark multi-omics DR approaches using: i) artificial multi-omics cancer data ii) multi-omics bulk data from 10 different cancer types downloaded from TCGA iii) multi-omics single-cell data from cancer cell lines In (i), the capability of the various methods to predict the clustering ground truth was found strongly sensible to the size of the clusters, with intNMF, RGCCA, MCIA and JIVE being the more robust methods. For (ii), MCIA, RGCCA, MOFA and JIVE more consistently identified factors associated to survival, clinical annotations and biological annotations. Finally in (iii), despite never being applied to single-cell data, tICA and MSFA outperformed other methods for their ability to cluster  single cells based on their cell line of origin. Overall, our results show that RGCCA, MCIA and JIVE perform consistently better across the three scenarios. This suggests that a mathematical formulation, based on the search of omic-specific factors whose inter-dependence is maximized, better approximates the nature of multi-omics data.

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(1) Institut de Biologie de l’Ecole Normale Superieure IBENS, France, (2) Aix Marseille University, INSERM, MMG, CNRS, France, (3) Aix Marseille University, CNRS, France


Single-cell transcriptome and chromatin accessibility data integration reveals cell specific signatures

Andrés Felipe is a PhD student at the German Cancer Research Center in Heidelberg, Germany.

Authors: Andres Quintero (1), Anne-Claire Kröger (2), Carl Herrmann (2)

The ability to integrate multiple layers of omics data will play an essential role in understanding the complex interplay of different molecular mechanisms that give rise to cellular diversity. In particular, single-cell multi-omics studies provide an enormously valuable source of information, allowing the characterization of different cell states under different biological contexts. However, the integration of distinct cellular modalities to disentangle the regulatory networks and pathways that explain cell identity is still a challenge.Here we introduce Integrative Iterative Non-negative Matrix Factorization (i2NMF), a computational method to dissect cell type associated signatures from multi-omics data sets. i2NMF takes full advantage of data sets with multiple modalities for the same sample or cell, defining cell type-specific features and discerning the shared and specific contribution of each omics type to the identification of different cell types. We applied i2NMF to an early human embryo single-cell multi-omics data set for which scRNA-seq and scATAC-seq profiles were available for every single cell, identifying master transcription factors at the morula and blastocyst stages. Finally, i2NMF is also able to integrate different modalities across multiple experiments. We used this functionality to extract cell-type specific molecular signatures from two complementary datasets of the mouse visual cortex, comprising scATAC-seq and scRNA-seq data. i2NMF was implemented on TensorFlow, presenting a scalable framework and allowing its efficient execution under multiple systems. Our results demonstrate that i2NMF is a useful tool to identify cell-type specific signatures and dissect their underlying molecular features.

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(1) German Cancer Research Center (DKFZ), Germany, (2) University Hospital Heidelberg, Germany


Linking signalling and metabolomic footprints with causal networks

Aurélien Dugourd is a PhD student in mechanistic modelling at JRC Combine, RWTH Aachen, Germany.

Aurélien Dugourd (1), Christoph Kuppe (1), Rafael Kramann (1), Julio Saez-Rodriguez (2)

Renal clear cell carcinomas (RCCC) are the result of a system-wide dysregulation of signaling and metabolic functions  originating from multiple factors. Characterizing cellular molecular machineries across multiple omic layers is a very powerful strategy to understand the cellular effects of such dysregulations. In this study, we performed metabolomics and phosphoproteomics from RCCC tissue in comparison to the non-cancerous kidney tissue in a cohort of 20 patients. In order to extract mechanistic information from these observations and to integrate both datasets, we developed a novel analysis pipeline. Phosphoproteomic abundance changes are used to estimate kinase activity changes across patients. Kinase activity estimations are then correlated with metabolite abundance changes. This points at possible interactions between signaling pathways and metabolism. We subsequently build a generic network integrating signaling pathways and metabolic reaction networks based on literature knowledge and databases. We use this signaling/metabolic network to identify paths across kinases and metabolic enzymes to link the correlated kinase activities and metabolites.
This provides potential mechanisms to explain the effect of deregulation of signaling on metabolism. Our approach was able to recover the structure canonical signaling pathway topologies and highlight specific connections between kinases and metabolite abundance deregulated in kidney tumor tissues. This pipeline allows to extract and compare mechanistic
information from metabolomic, phosphoproteomic (and potentially transcriptomic) data across many kidney cancer patients. This information can be used to select potential therapeutic targets to disrupt cancer specific cellular mechanisms, such as the SP1 kinase. Furthermore, the pipeline offers the advantage of being easily transferable in many different biological contexts.

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(1) RWTH Uniklinikum Aachen, Germany, (2) Heidelberg University, Germany


A network-based approach for the identification of multi-omics modules associated with complex human diseases

Maria Anna Wörheide is a PhD student at the Helmholtz Zentrum München in Germany.

Authors: Maria Anna Wörheide (1), Jan Krumsiek (2), Gabi Kastenmüller (1), Matthias Arnold (1)

Application of advanced high-throughput omics technologies have provided us with vast amounts of quantitative, highly valuable data. For complex, heterogeneous, and untreatable diseases such as Alzheimer’s disease (AD), the integration of different omics levels and their interconnections is desperately needed to understand the underlying molecular pathomechanisms and identify potential therapeutic targets. However, integrated, multivariable analyses of cross-omics data are not straightforward, and even if successfully applied, often lack a human comprehensible representation. Graph databases provide an intuitive and mathematically well defined framework to store and interconnect diverse biological domains in accessible network structures. Here, we propose a network-based, multi-omics framework
developed with the graph database Neo4j, that allows the large-scale integration and analysis of data on biological entities across omics, as well as results from association analysis with specific (endo) phenotypes. The backbone of this framework comes from known biological relationships and functional/pathway annotations available in public databases. It is augmented with experimental, quantitative data for single omics (e.g. tissue-specific gene expression) and across omics (e.g. eQTLs or mQTLs) derived in population-based studies. To identify modules within this network that are potentially relevant to a disease such as AD, we extend the
framework using large-scale association data for AD (e.g. from case-control GWASs). The resulting network is comprised of over 50 million nodes (entities), representing more than 30 different data types, and more than 80 million edges (relationships). We mined this comprehensive catalogue of biological information using established graph algorithms to
identify potentially disease-related modules of tightly interlinked entities, and were able to obtain several subnetworks significantly enriched for AD-associations.

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(1) Helmholtz Zentrum München, Germany, (2) Weill Cornell Medicine, United States of America


Mechanistic insights into transcription factor cooperativity and its impact on protein-phenotype interactions

Ignacio Ibarra is a PhD student in Judith Zaugg’s lab at EMBL Heidelberg, Germany.

Authors: Ignacio Ibarra, Nele Hollmann, Bernd Klaus, Sandra Augsten, Britta Velten, Janosch Hennig, Judith Zaugg (EMBL Heidelberg)

Recent high-throughput transcription factor (TF) binding assays revealed that TF cooperativity
is a widespread phenomenon. However, we still miss global mechanistic and functional understanding of TF cooperativity. To close this gap we introduce a statistical learning framework that provides structural insight into TF cooperativity and its functional consequences based on next generation sequencing data. We identify DNA shape as driver for cooperativity, with a particularly strong effect for Forkhead-Ets pairs. Follow-up experiments revealed a local shape preference at the Ets-DNA-Forkhead interface and a decreased cooperativity once the interaction is lost. Additionally, we discovered many novel functional associations for cooperatively bound TFs. Examining the novel link between FOXO1:ETV6 and lymphomas revealed that their joint expression levels improve patient survival stratification.
Altogether, our results demonstrate that inter-family cooperative TF binding is driven by position-specific DNA readout mechanisms, which provides an additional regulatory layer for downstream biological functions.

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Working on your own conference poster? Then check out 10 tips to create a scientific poster people want to stop by .

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How does the environment play a role in biodiversity?

Biodiversity – in all its forms and interactions – is the variety of life on Earth. Climate change is exacerbating biodiversity loss, and vice versa. Ahead of the EMBO | EMBL Symposium ‘The Organism and its Environment’ (1–4 March 2020), we talk to Scientific Organiser and EMBL Director General Edith Heard about the impact the environment has on biodiversity and the role of research in solving global challenges.

Does the environment play a large role in the creation of biological diversity?

Biodiversity is the variety of life on Earth. This life, in all its shapes and sizes, occurs in the context of ecosystems: it relies on and interacts with other organisms and the physical environment. Biodiversity represents the collective ‘knowledge learned’ by evolving species over millions of years, about how to survive the vastly varying environmental conditions Earth has and is experiencing. These varying environmental conditions cause natural variations in biodiversity, as well as genetic and epigenetic changes, within and between species over time. Today, scientists are trying to understand the basis of these natural variations, as they will allow us to understand how life evolves.

Fish populations have declined at an alarming rate, and half the world’s shallow water coral reefs have been lost in just 30 years.

But biodiversity is also a measure of the health of any ecosystem. Recent trends in biodiversity loss show very clearly that humans are destroying ecosystems on a massive scale. According to the Director General of the World Wildlife Fund (WWF), increased pollution, deforestation, climate change and other manmade factors have created a “mind-blowing” crisis. The WWF Living Planet Report 2018 (WWF LPR, 2018) also states that freshwater fish populations have declined by more than 80% on average since 1970 and half of the world’s shallow water coral reefs have been lost in the last 30 years (WWF LPR, 2018). Alongside this, deforestation of tropical rainforests means we are currently losing more than 100 species of plants and animals a day (Holley, 2017). In short, human’s influence on the environment greatly impacts biodiversity and we are currently burning the library of life.

How can you determine the effect of the environment on an organism?

The environment can affect an organism in a multitude of ways. The impact can be transient or longer term; within an individual or across generations. The environment can also lead to molecular, cellular, physiological or behavioural changes. For example, the expression of genes in an organism can be influenced by the external environment, such as where the organism develops or factors associated with where it is located. Gene expression could also be influenced by an organism’s internal environment, including hormones or metabolism. Finally, the genome itself – genetic factors that vary between individuals in natural populations – could also influence gene expression.

Research groups at EMBL look at how variety in organisms comes about

Untangling the impact of genetic and environmental variation can be very challenging and for a long time, scientists have tended to focus on minimising variations in the environment in order to understand how changes in genotype affect phenotype. This, alongside the deeply embedded “one genotype = one phenotype” metaphor, has meant that environmentally induced phenotypic variation has been ignored in favour of ‘‘more useful and precise’’ study of genetic polymorphisms. This is despite the fact that from as far back as the early 1900s, scientists have known that the phenotype of an individual depends on the interaction between its genotype and environmental cues! Today, we finally have the power to consider the impact of the environment on phenotype. We can make precise measurements at the molecular, cellular and organism scales in controlled environments that can be varied and we can sequence genomes at the same time.

We can also take human data paired with environmental data – for example in the context of some of EMBL’s research interests such as infectious disease and microbiomes – to understand the quantitative effects of the environment and its influence on human biology. Pioneering projects such as Tara Oceans have also allowed us to research the interactions between organisms and the environment by generating reference data, discovering emergent ecological principles and developing predictions about how ecosystems will be affected by a changing environment. Understanding how organisms exist together and in changing environments is of fundamental importance for our understanding of biological principles and our knowledge of life.

What challenges are currently being faced in this field?

Studying organisms in their environment will become increasingly important.

Understanding the behaviour of individual molecules, cells or whole organisms is already challenging. Understanding how the environment influences an organism – or populations of organisms – represents a whole new scale in complexity. This is an area that I think EMBL could uniquely contribute to in the future. It will be necessary to shift from researching organisms mainly in the laboratory to studying them in their environment. We will also need to ensure the rapid development of technologies and tools to meet these scientific needs. Alongside this, we need new approaches to integrate large, complex data sets and make sense of them. To rise up to this challenge, we need theory. We are now in a unique position to address the dynamics and complexity of living matter across multiple scales and in the context of changing environment. But we need theory to address societal and planetary issues too. We must aim for a rate of scientific discovery that outpaces the rate of calamity such as biodiversity loss, ecosystem degradation, epidemics and climate change.

What can be done to prepare for the future with regard to biological diversity, the organism and its environment?

Research, research and more research! Environmental problems such as the hole in the ozone layer or acid rain were solved by sound scientific approaches. We need to learn from these past scientific and societal successes. Today the ever-increasing numbers of new technologies are allowing us to collect, measure and store data at unprecedented scales. We also need to bring ecologists, zoologists, population geneticists and environmental experts together to address these research questions. Together we can apply cutting-edge technology with rigour, attract new scientific talent and disseminate knowledge to global communities.

What inspired you to organise this symposium?

As a geneticist and epigeneticist, I have explored the intersection between genotype and the environment and how that produces a phenotype. From observing many areas of research – ranging from social insects such as bees and ants, to plant vernalisation and variations between identical twins – I felt that the time is ripe to bring together scientists from many different areas. I also wanted this to be a symposium that would attract scientists from different areas to EMBL.

At EMBL, we want to understand the molecular basis of life. Until now, EMBL has been known for exploring genomic, molecular, structural and cell biology at the level of individual organisms. Looking ahead, we want to study organisms in the context of their physical and biological environments not just in isolation. In order to truly understand life on Earth, we need to study organisms in nature, not just in the lab. One way to understand life at the molecular level will be to try to bring relevant ecosystems back to the lab, to measure and perturb them under controlled conditions. The speakers we’ve invited are experts from many different areas of biology or ecology, and will bring exciting new perspectives to our research.

The EMBO|EMBL Symposium: The Organism and its Environment will take place at EMBL Heidelberg, Germany, from 1-4 March 2020

What is the greatest benefit of this symposium for the scientific community?

The symposium is an opportunity to address how organisms are influenced by a changing environment. It will bring together different research disciplines and go beyond pure genetic or ecological perspectives of phenotypic variation. Geneticists, molecular biologists, evolutionary biologists and ecologists do not necessarily meet under ordinary circumstances. This meeting will enable such interactions and cross-fertilisation.

What will be the main highlight of the symposium?

Today we are in a unique position to address the complexity and dynamics of life at multiple scales, from molecules to ecosystems. We also need to consider the idea that change including in the environment is not necessarily a bad thing. After all, without change, evolution could not occur and none of the amazing biodiversity of life on our planet would exist! I hope that a highlight of this symposium will be some wonderful new insights into evolutionary processes.

 

References

Holley D., (2017). General Biology II, Organisms and Ecology. Indianapolis: Dog Ear Publishing, 898.

World Wildlife Fund, (2018). Living Planet Report: Aiming higher [PDF] https://wwf.panda.org/knowledge_hub/all_publications/living_planet_report_2018/ [Accessed 25 July 2019].

https://wwf.panda.org/knowledge_hub/all_publications/living_planet_report_2018/

However the WWF DG is quoted by several articles as describing the crisis as mind-blowing, for example: “https://www.voanews.com/science-health/report-earth-has-lost-60-percent-its-wildlife-1970

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We’ve proved it, biologists can also program

“Like punning, programming is a play on words.” Alan J. Perlis.

You don’t have to be a programmer to have programming skills. Writing code is an essential part of being a programmer (duh!), but is also a vital component of being a scientific developer, software developer or computer scientist. You can utilise computer programs to automate tedious and repetitive tasks, extract results from experimental data, apply models to solve your research questions or purely have fun with your own projects.

Today is Programmers’ Day (yay!🥳) and we want to recognise all those who submerge themselves in the deepest mysteries of code (especially their own) and aim to automate the future.

If you’re looking to start venturing into the programming world or embark on your next project, get some inspiration from some scientists who are helping out at our EMBL Events’ courses.

Florian Huber PHOTO: Marietta Schupp/EMBL

“What do I love about programming? It allows me to go from zero to one: gaining new biological insights from data.” Florian Huber (Postdoctoral Fellow, at the Typas Group in EMBL Heidelberg and the Beltrao Group at EMBL–EBI in Hinxton).

 

 

 

 

Ullrich Köthe PHOTO: Ullrich Köthe

“Automated image analysis has always been an interesting and fun field of research, but thanks to the deep learning revolution and the wide availability of wonderful neural network libraries, we can now actually solve hard practical problems.” Ullrich Köthe (Group Leader in the Visual Learning Lab Heidelberg).

 

 

Valentyna Zinchenko PHOTO: Carolina Cuadras/EMBL

“Programming skills allow you to automate the routineparts of your job and focus more on the exciting ones. At some moment you just have so much data, that you would not want to process it manually. You would not wash your clothes by hand if you have a washing machine, would you? Then why analyzing your data manually, when you can have it done by a machine as well?” Valentyna Zinchenko (Predoctoral Fellow in the Kreshuk Group).

 

Adrian Wolny PHOTO: Carolina Cuadras/EMBL

“Whenever I build something, be it a new machine learning model or my pet project, I always try to make it easy to understand and generic enough so that other people could use it in their work. I try to open source my projects whenever I can and contribute back to the community. There is nothing more rewarding than seeing your little piece of software used by others to find answers to their own research questions.” Adrian Wolny (Visiting Researcher at EMBL and PhD candidate at Heidelberg University).

 

Pavel Baranov PHOTO: Pavel Baranov

“The relationship between computer science and modern biology is akin to that between mathematics and physics.” Pavel Baranov (Professor of Biomolecular Informatics, University College Cork, Ireland)

 

 

 

 

It’s no secret that managing biological data efficiently can be overwhelming and feel impossible. If you’re a biologist who’s interested in learning how to process, analyse, organise and interpret your almost innumerable data sets – preferably with the most suitable and state-of-the-art techniques and tools out there – EMBL Events has got you covered.

EMBL Course: Deep Learning for Image Analysis, Apply by 20 September 2019

EMBL Course: Exploratory Analysis of Biological Data: Data Carpentry, Apply by 5 November 2019

EMBL Course: Analysis and Integration of Transcriptome and Proteome Data, Apply by 10 November 2019

EMBL Course: Immune Profiling of Single Cells, Apply by 10 November 2019

EMBO Practical Course: Microbial Metagenomics: A 360º Approach, Apply by 27 January 2020

EMBO Practical Course: Measuring Translational Dynamics by Ribosome Profiling, Apply by 9 February 2020

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