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Battery energy storage systems (BESS) can be used for ancillary services like frequency containment reserve (FCR), which can generate a significantly higher revenue than energy arbitrage. Different FCR services differ in revenues and energy throughput, which induces costs due to conversion losses, tariffs, but it also leads to a significant number of battery cycles that reduce the battery capacity over time. The normal operation reserve (FCR-N) had the highest revenues in the past years, but comes along with a higher energy throughput than the disturbance reserve (FCR-D) which also has a lower price. - Based on the Nordic regulatory frame work with 5 years of market and tariff data, the present study demonstrates that by choosing the most profitable service for each hour it is possible to reduce the number of charge cycles with 51% and increase the operating profit with 22% compared to delivering pure FCR-N.

This paper presents the experimental validation of a lithium-iron phosphate cell model. The modelling of dynamic cell behaviour is crucial to improve the performance of reconfigurable battery systems, in which monitoring of the dynamics allows more resoluted leveraging of the battery cells. However, the models of lithium-ion cells are generally inaccurate due to nonlinearities, measurement noise and because the most descriptive state, the state of charge is hidden. Furthermore, the parameter identification of the model requires time and precise measurements, while they differ among the cells, and change as the cells age. The burden of the detailed modelling of a battery system can be alleviated by modelling a single cell, and using the model for each cell in the system. In this work, this possibility is explored by validating a single-cell reference model for a reconfigurable battery system. The terminal voltage residual (error between model and measurement) is presented, and its correlations with internal and external variables are investigated. These correlations can also be used to alleviate the modelling errors. It is concluded that the reference model can qualitatively describe the cell behaviour. By applying small modifications, the model could be used for online estimation.

Battery energy storage systems (BESSs) are known as a potential solution to integrate renewables and electric vehicle (EV) charging in the power system. This article compares the direct grid installation of ultra-fast chargers (UFCs) with a hybrid system inclusive of a reconfigurable BESS, a photovoltaic (PV) unit, two UFCs and a grid connection. The hybrid system is simulated with an optimization model, which reveals that the overall efficiency of the system plays a major role in determining the power grid exchange. Results show that the hybrid system can increase the local PV consumption while reducing the grid impact of EV charging. Based on yearly results, the hybrid system shows potential for further improving the utilization of the BESS and unlocking new revenue streams.

Self-sufficiency is an important metric for various energy concepts, as it reflects what share of the local consumption is covered by local generation. However, the equation commonly used in literature cannot be applied to systems with an energy storage that actively exchanges energy with the grid. With more and more systems incorporating storage units it is therefore necessary to re-think the mathematical definition of self-sufficiency. The present paper addresses this issue by proposing an alternative equation that captures distinctive factors introduced by storage units: (i) Energy exported to the grid can originate from previously imported energy, (ii) initial and final storage energy in a given observation period can be different, (iii) the usage of storage systems entails energy losses. It is demonstrated that neglecting these factors leads to an over- or underestimation of self-sufficiency with values even reaching below 0 % or above 100 %. In contrast, the self-sufficiency calculated by the proposed definition considers the above mentioned factors and always stays within the defined range.

The paper provides a detailed description of the 62-kWh battery pack of the Nissan LEAF e-plus. Experimental measurements are collected and analyzed to identify electrical and thermal properties. The parameters identified are open circuit voltage, polarization resistance, diffusion resistances and capacitances. Measurements are carried out for different Stateof-Charge and temperatures values. The current interruption method is used to identify the properties of the battery, since it is an effective way to analyze the whole battery pack without disassembling the vehicle. Afterwards, a cooldown analysis is described to identify thermal properties such as thermal capacitance and resistance. The paper is concluded with an early-stage assessment of the degradation of the battery pack after 1.5 years by using on-board readings of State-of-Health, temperature, and State-of-Charge. Stepwise changes in the State-of-Health are observed every 90 days superimposed to the expected degradation trend.

Reconfigurable batteries can change their cell topology in real time, which enables them to adapt their voltage during operation. This unique capability makes interfacing power converters redundant in applications where batteries are directly coupled with other DC components. The present paper characterizes a prototype of a reconfigurable battery for high power applications, and estimates the efficiency for the complete operating area. The results show that the efficiency is higher during charging and for higher voltage levels. The power losses of the battery components enabling the reconfigurable design only add a minor contribution to the overall losses. Furthermore, the highest efficiencies are achieved at low power values, where DC-DC converters generally show a steep decrease. Hence, this novel battery design is expected to have a better efficiency compared to a conventional battery with power converter.

The accumulation of surface charges is a crucial challenge, especially for HVDC components. Accumulated surface charges can change the electric field distribution and generate weak points, especially in case of superimposed transient voltages and, therefore lower the performance e.g. of insulators. Hence, an accurate measurement of the surface potential and so the surface charges is necessary to optimize these components. Commonly, the surface potential is measured with an electrostatic voltmeter. In this study a procedure for determining the spatial impulse response of a compensating electrostatic voltmeter depending on only the surface to probe distance is presented. Based on the performed measurements a mathematical model is developed to describe the capacitive influence and significance of the local surface potential on the measurement result. The actual measurement value is a weighted and averaged value given by the actual position and its surrounding, which is also confirmed by numerical simulations. The performed procedure enables high accuracy of the measurement of surface potentials and so of surface charges using different types of electrostatic voltmeters and shows the limitation of the measurement procedure. This knowledge increases the possibility to design optimized components for HVDC systems.

Batteries are key components of future power systems with high shares of renewables. Their fast response enable them to contribute to one of the most crucial ancillary services - frequency containment reserve. However, longer periods with biased frequency pose challenges for batteries due to their limited energy capacity. This is particularly crucial in the Nordic synchronous area where 100% certainty of delivery is required. The present study uses a simulation model with three years of historical frequency, market, and tariff data, to compare three energy management strategies that comply with the Nordic regulatory framework. The first two strategies both utilize an hourly adjustment of the reference power to, on average, recover the energy level to a desired value. In the first strategy, this energy is traded on the intraday market, while in the second strategy it is settled via the balancing market. The third strategy is based on an exemption agreement with the Danish transmission system operator. Since capacity payment is the strongest factor that determines the profit, the study derives maximum regulating power and annual profit as a function of the energy/power capacity ratio and the efficiency of the storage system. The highest regulating power and profit can be achieved when applying the exemption agreement. Where this agreement is not available, the battery operator should apply the second strategy and settle the energy costs through the balancing market. Trading the energy on the intraday market slightly reduces the energy costs, but allows for significantly lower regulating power and revenues.

Hybrid fast-charging stations with battery storage and local renewable generation can facilitate low-carbon electric vehicle (EV) charging, while reducing the stress on the distribution grid. This paper proposes energy management strategies for a novel multi-battery design that directly connects its strings to other DC components through a busbar matrix without the need for interfacing power converters. Hence, the energy management system has two degrees of control: (i) allocating strings to other DC microgrid components, in this case a photovoltaic system, two EV fast chargers, and a grid-tie inverter, and (ii) managing the energy exchange with the local distribution grid. For the grid exchange, a basic droop control is compared to an enhanced control including forecasts in the decision making. To this end, this paper evaluates results from multiple Monte Carlo simulations capturing the uncertainty of EV charging. For a realistic charging behaviour in each simulation run, random fast-charging profiles were created based on probability distributions of actual fast-charging data for arrival time, charging duration, and requested energy. The impact of different utilisation levels of the chargers was assessed by varying the average charging instances from 1 to 30 EVs per day. Using actual photovoltaic measurements from different months, the numerical analyses show that the enhanced control increases self-sufficiency by reducing grid exchange, and decreases the number of battery cycles. However, the enhanced control operates the battery closer to its charge limits, which may accelerate calendar ageing., Comment: Preprint submitted to Elsevier eTransportation

DNA methylation is a crucial, abundant mechanism of gene regulation in vertebrates. It is less prevalent in many other metazoan organisms and completely absent in some key model species, such as D. melanogaster and C. elegans. We report here a comprehensive study of the presence and absence of DNA methyltransferases (DNMTs) in 138 Ecdysozoa, covering Arthropoda, Nematoda, Priapulida, Onychophora, and Tardigrada. Three of these phyla have not been investigated for the presence of DNA methylation before. We observe that the loss of individual DNMTs independently occurred multiple times across ecdysozoan phyla. We computationally predict the presence of DNA methylation based on CpG rates in coding sequences using an implementation of Gaussian Mixture Modelling, MethMod. Integrating both analysis we predict two previously unknown losses of DNA methylation in Ecdysozoa, one within Chelicerata (Mesostigmata) and one in Tardigrada. In the early-branching Ecdysozoa Priapulus caudatus we predict the presence of a full set of DNMTs and the presence of DNA methylation. We are therefore showing a very diverse and independent evolution of DNA methylation in different ecdysozoan phyla spanning a phylogenetic range of more than 700 million years.

The paper presents the scope and research activities, both analytical and experimental, to be carried out on the Danish Island of Bornholm under the 4-year (2019-2023) H2020 Insulae project. The two use cases taking place in Denmark are described. The first use case is dedicated to modelling and testing a low-voltage DC microgrid comprising a battery storage, renewable energy sources, and an EV fast charger, towards providing grid services. The second use case investigates the potential of a renewable-driven virtual power plant embracing different energy domains (electrical, heat, gas, transportation) for flexibility provision to the islanded energy system. Planned research activities for both use cases are described along with results in terms of design and engineering.

Non-enzymatic short-chain XNA replication is often prohibited due to product inhibition, and product inhibition has been one of the major stumbling blocks for implementing prebiotic information replication systems both in bulk 4 and as part of synthetic protocells. 7 Product inhibition implies that a newly formed complementary template is very unlikely to dehybridize from the template. However, Gibbs-Davis and her team 1 have developed a method to circumvent product inhibition based on mismatches and lesions between the complementary templates that destabilize them and thus enables a continued replication process. In this work we explore in simulation the thermodynamic and kinetic properties of lesion induced DNA amplification processes. The method we use focuses on a characterization of the oligomers by their free energies rather than by their detailed base-pair structure.

In this study, we introduce a battery energy storage system (BESS) with reconfigurable cell topology as the direct power source for fast-charging of electric vehicles (EVs). In the proposed scenario, the BESS is following the charging request of the EV by changing its cell topology in a real time fashion. The BESS is modelled at the cell level in order to demonstrate the reconfigurable design, and linked with an EV model. The simulation results confirm that the BESS can maintain a balanced level of its cell states while following the voltage request of the EV with satisfactory precision. However, the approach of adaptive cell switching shows to be not sufficient for fulfilling the current request. Therefore, complementary solutions are necessary to achieve a suitable control of the charging current.

Nanostructured noble-metal catalysts traditionally suffer from sintering under high operating temperatures, leading to durability issues and process limitations. The encapsulation of nanostructured catalysts to prevent loss of activity through thermal sintering, while maintaining accessibility of active sites, remains a great challenge in the catalysis community. Here, we report a robust and regenerable palladium-based catalyst, wherein palladium particles are intercalated into the three-dimensional framework of SBA-15-type mesoporous silica. The encapsulated Pd active sites remain catalytically active as demonstrated in high-temperature/pressure phenol hydrodeoxygenation reactions. The confinement of Pd particles in the walls of SBA-15 prevents particle sintering at high temperatures. Moreover, a partially deactivated catalyst containing intercalated particles is regenerated almost completely even after several reaction cycles. In contrast, Pd particles, which are not encapsulated within the SBA-15 framework, sinter and do not recover prior activity after a regeneration procedure.

Understanding the deactivation of transition-metal carbide catalysts during hydrodeoxygenation (HDO) reactions is of great importance for improving the production of the second generation fuels from biomass. Based on a combined experimental and theoretical study, we present a mechanistic model for the deactivation of molybdenum carbide catalysts during phenol HDO in the presence of water. At increased water pressure, water molecules preferentially bind to the surface, and active sites are no longer accessible for phenol. In line with first principle calculations, experiments reveal that this process is fully reversible because the reduction of the water partial pressure results in a threefold increase in conversion. The direct deoxygenation of phenol was calculated to be the most favorable pathway, which is governed by the structure of the phenol adsorption complex on the surface at high hydrogen coverage. This is consistent with the experimentally observed high benzene selectivity (85 %) for phenol HDO over MoCx/HCS (hollow carbon spheres) catalyst.

A simple and efficient hydrodeoxygenation strategy is described to selectively generate and separate high-value alkylphenols from pyrolysis bio-oil, produced directly from lignocellulosic biomass. The overall process is efficient and only requires low pressures of hydrogen gas (5 bar). Initially, an investigation using model compounds indicates that MoCx/C is a promising catalyst for targeted hydrodeoxygenation, enabling selective retention of the desired Ar−OH substituents. By applying this procedure to pyrolysis bio-oil, the primary products (phenol/4-alkylphenols and hydrocarbons) are easily separable from each other by short-path column chromatography, serving as potential valuable feedstocks for industry. The strategy requires no prior fractionation of the lignocellulosic biomass, no further synthetic steps, and no input of additional (e.g., petrochemical) platform molecules.

Growing evidence shows that epigenetic mechanisms contribute to complex traits, with implications across many fields of biology. In plant ecology, recent studies have attempted to merge ecological experiments with epigenetic analyses to elucidate the contribution of epigenetics to plant phenotypes, stress responses, adaptation to habitat, and range distributions. While there has been some progress in revealing the role of epigenetics in ecological processes, studies with non-model species have so far been limited to describing broad patterns based on anonymous markers of DNA methylation. In contrast, studies with model species have benefited from powerful genomic resources, which contribute to a more mechanistic understanding but have limited ecological realism. Understanding the significance of epigenetics for plant ecology requires increased transfer of knowledge and methods from model species research to genomes of evolutionarily divergent species, and examination of responses to complex natural environments at a more mechanistic level. This requires transforming genomics tools specifically for studying non-model species, which is challenging given the large and often polyploid genomes of plants. Collaboration among molecular geneticists, ecologists and bioinformaticians promises to enhance our understanding of the mutual links between genome function and ecological processes.

The importance of RNA-based regulation is becoming more and more evident. Genome-wide sequencing efforts have shown that the majority of the DNA in eukaryotic genomes is transcribed. Advanced high-throughput techniques like CLIP for the genome-wide detection of RNA-protein interactions have shown that post-transcriptional regulation by RNA-binding proteins matches the complexity of transcriptional regulation. The need for a specialized and integrated analysis of RNA-based data has led to the foundation of the RNA Bioinformatics Center (RBC) within the German Network of Bioinformatics Infrastructure (de.NBI). This paper describes the tools, services and databases provided by the RBC, and shows example applications. Furthermore, we have setup an RNA workbench within the Galaxy framework. For an easy dissemination, we offer a virtualized version of Galaxy (via Galaxy Docker) enabling other groups to use our RNA workbench in a very simple way.

Several classes of exclusively--or at least predominantly--unspliced non-coding RNAs have been described in the last years, including totally and partially intronic transcripts and long intergenic RNAs. Functionally, they appear to be involved in regulating gene expression, at least in part by associating with the chromatin. Intron-less transcripts have received little attention, even though recent findings indicate that intron-less protein-coding genes have several features that set them apart from the more abundant and much better understood spliced mRNAs. Even less is known about unspliced non-coding transcripts. Thus we systematically analyze the distribution of unspliced ESTs in the human genome. These form a large source of transcriptomic data that is almost always excluded from detailed studies. Most unspliced ESTs appear in clusters overlapping, or located in the close vicinity of, annotated RefSeq genes. Partially intronic unspliced ESTs show complex patterns of overlap with the intron/exon structure of the RefSeq gene. Distinctive patterns of CAGE tags indicate that a large class of unspliced EST clusters is forming long extensions of 3'UTRs, at least several hundreds of which probably appear also as independent 3'UTR-associated RNAs.

Although subtypes of pancreatic ductal adenocarcinoma (PDAC) have been described, this malignancy is clinically still treated as a single disease. Here we present patient-derived models representing the full spectrum of previously identified quasi-mesenchymal (QM-PDA), classical and exocrine-like PDAC subtypes, and identify two markers--HNF1A and KRT81--that enable stratification of tumors into different subtypes by using immunohistochemistry. Individuals with tumors of these subtypes showed substantial differences in overall survival, and their tumors differed in drug sensitivity, with the exocrine-like subtype being resistant to tyrosine kinase inhibitors and paclitaxel. Cytochrome P450 3A5 (CYP3A5) metabolizes these compounds in tumors of the exocrine-like subtype, and pharmacological or short hairpin RNA (shRNA)-mediated CYP3A5 inhibition sensitizes tumor cells to these drugs. Whereas hepatocyte nuclear factor 4, alpha (HNF4A) controls basal expression of CYP3A5, drug-induced CYP3A5 upregulation is mediated by the nuclear receptor NR1I2. CYP3A5 also contributes to acquired drug resistance in QM-PDA and classical PDAC, and it is highly expressed in several additional malignancies. These findings designate CYP3A5 as a predictor of therapy response and as a tumor cell-autonomous detoxification mechanism that must be overcome to prevent drug resistance.

Background Despite their abundance, unspliced EST data have received little attention as a source of information on non-coding RNAs. Very little is know, therefore, about the genomic distribution of unspliced non-coding transcripts and their relationship with the much better studied regularly spliced products. In particular, their evolution has remained virtually unstudied. Results We systematically study the evidence on unspliced transcripts available in EST annotation tracks for human and mouse, comprising 104,980 and 66,109 unspliced EST clusters, respectively. Roughly one third of these are located totally inside introns of known genes (TINs) and another third overlaps exonic regions (PINs). Eleven percent are “intergenic”, far away from any annotated gene. Direct evidence for the independent transcription of many PINs and TINs is obtained from CAGE tag and chromatin data. We predict more than 2000 3’UTR-associated RNA candidates for each human and mouse. Fifteen to twenty percent of the unspliced EST cluster are conserved between human and mouse. With the exception of TINs, the sequences of unspliced EST clusters evolve significantly slower than genomic background. Furthermore, like spliced lincRNAs, they show highly tissue-specific expression patterns. Conclusions Unspliced long non-coding RNAs are an important, rapidly evolving, component of mammalian transcriptomes. Their analysis is complicated by their preferential association with complex transcribed loci that usually also harbor a plethora of spliced transcripts. Unspliced EST data, although typically disregarded in transcriptome analysis, can be used to gain insights into this rarely investigated transcriptome component. The frequently postulated connection between lack of splicing and nuclear retention and the surprising overlap of chromatin-associated transcripts suggests that this class of transcripts might be involved in chromatin organization and possibly other mechanisms of epigenetic control. Electronic supplementary material The online version of this article (doi:10.1186/s12862-015-0437-7) contains supplementary material, which is available to authorized users.

Pancreatic ductal adenocarcinoma (PDAC) is a very aggressive disease with poor prognosis. Treatment with gemcitabine, the FOLFIRINOX scheme or nab-paclitaxel offer only a modest increase in overall survival. For a number of other carcinomas, tumor subtypes have been uncovered that allow the use of targeted therapies. Although subtypes of PDAC were described, this malignancy is clinically still treated as a single disease. We established patient-derived models representing the full spectrum of previously identified quasi-mesenchymal (QM-PDA), classical and exocrine-like PDAC subtypes, and identified two markers—HNF1A and KRT81—that enable stratification of tumors into different subtypes by immunohistochemistry. Patients bearing tumors of these subtypes show significant differences in overall survival and their tumors differ in drug sensitivity, with the exocrine-like subtype being resistant to tyrosine kinase inhibitors and paclitaxel. The xenobiotic enzyme, cytochrome P450 3A5 (CYP3A5), metabolizes these compounds in tumors of the exocrine-like subtype, and pharmacological or short hairpin RNA (shRNA)-mediated CYP3A5 inhibition sensitizes tumor cells to these drugs. Additionally, retrospective analysis of a large patient cohort confirmed that CYP3A5 is predominantly found in those patient tumors classified as exocrine-like. Whereas the hepatocyte nuclear factor 4, alpha (HNF4A) controls basal expression of CYP3A5, drug-induced CYP3A5 upregulation is mediated by the nuclear receptor NR1I2. Interfering with these regulatory mechanisms may provide an alternative approach to suppress the CYP3A5 pathway. CYP3A5 also contributes to acquired drug resistance in QM-PDA and classical PDAC, and is highly expressed in several additional malignancies. These findings designate CYP3A5 as predictor of therapy response and as a tumor cell-autonomous detoxification mechanism that must be overcome to prevent drug resistance. Citation Format: Elisa M. Noll, Christian Eisen, Albrecht Stenzinger, Elisa Espinet, Alexander Muckenhuber, Corinna Klein, Vanessa Vogel, Bernd Klaus, Wiebke Nadler, Christoph Rösli, Christian Lutz, Michael Kulke, Jan Engelhardt, Franziska Zickgraf, Octavio Espinosa, Matthias Schlesner, Xiaoqi Jiang, Annette Kopp-Schneider, Peter Neuhaus, Marcus Bahra, Bruno V. Sinn, Roland Eils, Nathalia A. Giese, Thilo Hackert, Oliver Strobel, Jens Werner, Markus W. Büchler, Wilko Weichert, Andreas Trumpp, Martin R. Sprick.{Authors}. CYP3A5 mediates basal and acquired therapy resistance in different subtypes of pancreatic ductal adenocarcinoma. [abstract]. In: Proceedings of the AACR Special Conference on Pancreatic Cancer: Advances in Science and Clinical Care; 2016 May 12-15; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2016;76(24 Suppl):Abstract nr B77.

Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive disease with poor prognosis. Treatment with gemcitabine, the FOLFIRINOX scheme or nab-paclitaxel offer only a modest increase in overall survival. For a number of other carcinomas, tumor subtypes have been uncovered that allow the use of targeted therapies. Although subtypes of PDAC were described, this malignancy is clinically still treated as a single disease. We established patient-derived models representing the full spectrum of previously identified quasi-mesenchymal (QM-PDA), classical and exocrine-like PDAC subtypes, and identified two markers—HNF1A and KRT81—that enable stratification of tumors into different subtypes by immunohistochemistry. Patients bearing tumors of these subtypes show significant differences in overall survival and their tumors differ in drug sensitivity, with the exocrine-like subtype being resistant to tyrosine kinase inhibitors and paclitaxel. The xenobiotic enzyme, cytochrome P450 3A5 (CYP3A5), metabolizes these compounds in tumor cells of the exocrine-like subtype, and pharmacological or short hairpin RNA (shRNA)-mediated CYP3A5 inhibition sensitizes tumor cells to these drugs. Additionally, retrospective analysis of a large patient cohort confirmed that CYP3A5 is predominantly found in those patient tumors classified as exocrine-like (Noll, Eisen et al., Nature Medicine (2016) accepted). Whereas the hepatocyte nuclear factor 4, alpha (HNF4A) controls basal expression of CYP3A5, drug-induced CYP3A5 upregulation is mediated by the nuclear receptor NR1I2. Interfering with these regulatory mechanisms may provide an alternative approach to suppress the CYP3A5 mediated resistance pathway. CYP3A5 also contributes to acquired drug resistance in QM-PDA and classical PDAC in vitro and in vivo. Finally, CYP3A5 is highly expressed in several additional malignancies including hepatocellular and cervical carcinomas raising the possibility that the CYP3A5 resistance mechanism is operational in a variety of human cancers. These findings designate CYP3A5 as predictor of therapy response and as a tumor cell-autonomous detoxification mechanism that must be overcome to prevent drug resistance. Citation Format: Elisa M. Noll, Christian Eisen, Albrecht Stenzinger, Elisa Espinet, Alexander Muckenhuber, Corinna Klein, Vanessa Vogel, Bernd Klaus, Wiebke Nadler, Christoph Rösli, Christian Lutz, Michael Kulke, Jan Engelhardt, Franziska Zickgraf, Octavio Espinosa, Matthias Schlesner, Xiaoqi Jiang, Annette Kopp-Schneider, Peter Neuhaus, Marcus Bahra, Bruno Sinn, Roland Eils, Nathalia Giese, Thilo Hackert, Oliver Strobel, Jens Werner, Markus W. Büchler, Wilko Weichert, Andreas Trumpp, Martin R. Sprick. CYP3A5 mediates basal and acquired therapy resistance in different subtypes of pancreatic ductal adenocarcinoma. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr LB-120.

Functional RNA elements can be embedded also within exonic sequences coding for functional proteins. While not uncommon in viruses, only a few examples of this type have been described in some detail for eukaryotic genomes. Here we use RNAz and RNAcode, two comparative genomics methods that measure signatures of stabilizing selection acting on RNA secondary structure and peptide sequence, resp., to survey the fruit fly genomes. We estimate that there might be on the order of 1000 loci that are subject to dual selection pressure. The used genome-wide screens also expose the limitations of the currently available methods.

Instant-Grid (2006) provides an environment for demonstration, test and development of grid applications. Using a live-CD approach, cluster configuration and deployment of grid middleware is fully automated. The default installation of Instant-Grid results in a set of ready-to-use grid functionalities, which can be accessed in a beginner-friendly way via a Web portal. It also includes a number of p reconfigured applications, which demonstrate the uses and benefits of the grid. One example is the generation of photo realistic images using the grid as a rendering farm

Highlights • We have developed a novel method to determine 5hmC in CpG sequences. • The method uses the DNA methylation activity of DNMT1. • The method can be applied to about 90% of the mouse and human genomes. • Dynamic changes in 5hmC and 5mC were successfully monitored., Hydroxymethylcytosine has been shown to be involved in DNA demethylation and gene expression. Although methods to determine the position of hydroxymethylcytosine at single-base resolution have been reported, these methods involve some difficulties. Here, we report a simple method to analyze hydroxymethylcytosine in the CpG sequence utilizing the maintenance DNA methylation activity of DNMT1, which selectively methylates hemi-methylated but not hemi-hydroxymethylated CpG sequences. The method enables monitoring of the dynamics of the hydroxymethylation state of a specific genome site.

Research in evolutionary biology has been progressively influenced by big data such as massive genome and transcriptome sequencing data, scalar measurements of several phenotypes on tens to thousands of individuals, as well as from collecting worldwide environmental data at an increasingly detailed scale. The handling and analysis of such data require computational skills that usually exceed the abilities of most traditionally trained evolutionary biologists. Here we discuss the advantages, challenges and considerations for organizing and running bioinformatics training courses of 2–3 weeks in length to introduce evolutionary biologists to the computational analysis of big data. Extended courses have the advantage of offering trainees the opportunity to learn a more comprehensive set of complementary topics and skills and allowing for more time to practice newly acquired competences. Many organizational aspects are common to any course, as the need to define precise learning objectives and the selection of appropriate and highly motivated instructors and trainees, among others. However, other features assume particular importance in extended bioinformatics training courses. To successfully implement a learning-by-doing philosophy, sufficient and enthusiastic teaching assistants (TAs) are necessary to offer prompt help to trainees. Further, a good balance between theoretical background and practice time needs to be provided and assured that the schedule includes enough flexibility for extra review sessions or further discussions if desired. A final project enables trainees to apply their newly learned skills to real data or case studies of their interest. To promote a friendly atmosphere throughout the course and to build a close-knit community after the course, allow time for some scientific discussions and social activities. In addition, to not exhaust trainees and TAs, some leisure time needs to be organized. Finally, all organization should be done while keeping the budget within fair limits. In order to create a sustainable course that constantly improves and adapts to the trainees’ needs, gathering short- and long-term feedback after the end of the course is important. Based on our experience we have collected a set of recommendations to effectively organize and run extended bioinformatics training courses for evolutionary biologists, which we here want to share with the community. They offer a complementary way for the practical teaching of modern evolutionary biology and reaching out to the biological community.