Dragon09/odtu_chatbot huggingface dataset:
rewriting the ubiquitin code manipulating polyubiquitin chain linkage to investigate ubiquitin signalling in genome maintenance and beyond

ubiquitylation is an essential posttranslational modification that governs the activities and interactions of cellular proteins the structural diversity of polyubiquitin chains collectively called the ubiquitin code is thought to determine the fate of the modified proteins although many analytical and inhibitory ubiquitinspecific reagents exist we lack the tools to create polyubiquitin chains of defined linkage on a protein of interest in cells to investigate their signalling functions we recently established a method to induce substratespecific polyubiquitylation via three major linkages m1 k48 and k63 based on this technology we now propose to develop a new generation of research tools for the scientific community this will include the identification and design of custom enzymes for assembling the rarer still poorly characterised noncanonical linkages and a functionalisation with modules for chain editing branching and the identification of effectors in a combination of biochemical cell biological and proteomic approaches we will then apply these tools to major genome maintenance pathways with prominent roles in the defence against disorders such as cancer and premature ageing specifically we will analyse the significance of noncanonical polyubiquitylation in the response to dna doublestrand breaks and the interplay between degradative and nondegradative ubiquitylation in the regulation of essential dna replication and repair factors we envision that our research will not only provide new insight into ubiquitin signalling in genome maintenance but the new technology developed in this project will facilitate future investigations of polyubiquitin chains their readers and their writers in other signalling pathways situated at the interface between proteostasis and genome maintenance this project will thus advance our understanding of two essential cellular surveillance systems with critical functions in human health and wellbeing
learning and modeling the molecular response of single cells to drug perturbations

advances in singlecell genomics scg allow us to read out a cells molecular state with unprecedented detail increasingly so across perturbations to fully understand a cellular system one must be able to predict its internal state in response to all perturbations yet such modeling in scg is currently limited to descriptive statistics building upon my expertise in machine learning i propose to systematically model a cells behavior under perturbation focusing on the largely untouched area of druginduced perturbations with multiomics scg readouts a sufficiently generic model will predict perturbed cellular states enabling the design of optimal treatments in new celltypes in a pilot study we predicted gene expression changes of a cell ensemble in response to stimuli deepcell builds upon this approach based on a multicondition multimodal deeplearning approach for both normal and spatiallyresolved genomics we will set up a constrained interpretable model for the cellular expression response to diverse perturbations the added flexibility of the deepcell model versus classical smallscale systems biology models will allow us to interrogate the effects of combined drug stimuli and characterize the gene regulatory landscape by interpretation of the learned deep networkdeepcell provides unique possibilities to capitalize on cellbased drug screens to address fundamental questions in gene regulation and predicting treatment outcomes as a proof of concept i will identify targets that regulate enteroendocrine lineage selection in the intestine i will set up a 500compound singlecell organoid rnaseq screen based on compounds from a spatial imaging screen across 200000 intestinal organoids both of which we will model with deepcell we will leverage those models to predict optimal treatment for obese mice deepcell opens up the possibility of in silico drug screens with the potential to expedite drug discovery and impact clinical settings
tensors and neural networks for computational creativity

creativity in language is ubiquitous it is abundantly present in work with an explicit creative intention such as literary novels or poems but weighty doses of creativity also pervade everyday language use we believe that a computational model of creativity that focuses on language will shed light on the enigmatic processes and interactions that come into play when we humans express ourselves in creative ways moreover natural language generation systems in order to produce realistic utterances need to be endowed with a certain capacity for creativity the main goal of this research project is to develop unsupervised models of language that exhibit creativity in order to do so we propose an integrated approach that combines a number of important and innovative techniques first of all we rely on constructs from linear algebra called tensors in order to express language content according to different parameters using tensors we are able to induce latent semantics from multiway cooccurrences of textual content which can subsequently be used for the generation of creative expressions secondly we rely on advanced machine learning techniques notably neural networks neural network techniques have recently shown impressive performance in a number of natural language processing tasks yet these techniques are mainly mimicking human language production and thus are showing little creativity in language generation by adapting neural network approaches in various ways as well as integrating them with our tensorbased approach we expect to develop algorithms that are able to grasp the meaning of textual content in a more profound and elaborate way and at the same time are able to express it with creative intent the project has the potential for groundbreaking results not only because it would deepen our understanding of creativity but also because of practical applications within the field of natural language processing
a new drug to treat triple negative breast cancer

rnuucell is developing a new drug to treat triple negative breast cancer tnbc for which there is not any specific and efficient treatment in the market making this disease an unmet clinical needthe aggressivity of tnbc is due to the easiness of its metastization expanding the cancer through the body inevitably leading to death so far we gathered a set of results showing the antimetastatic potential of our new drug which mode of action would conceptually be able to eliminate the deadliest feature of cancer cells their ability to invade and metastasize this happens because the target of our drug is the cells foundation ie the cytoskeleton thus destroying the cytoskeleton of cells is like shaking the foundations of a house it will be tumbledownwith the women techeu program we will consolidate the proofofconcept of the drugs efficiency against metastases through two sets of in vivo studies in nude mice and we will start the preclinical studies by performing pharmacokinetics drug absorption distribution metabolism and excretion also in view of the natural future development of our drug we will start to develop its synthesis scaleup from the milligram to the multigram scale women techeu program mentoring and coaching will be also key to consolidate our business plan and to approach partners and investors towards a fundraising level a in the near future this level of funding 1 m will enable to finish our preclinical studies and place rnuucell in the position to license its international patent one of the companys assets pt108082b ea038640b1 ep3227307b1 cn107466297b jp6726678b2 us15533289 under examination on canada brazil and india to a pharmaceutical company using a businesstobusiness strategy
measuring illegal online pharmacies impact and coevolution

the pharma analytics market reached 60b in revenues in 2021 and is expected to grow at a 20 annual rate in the coming years the data and business intelligence provided by pharma analytics companies around drug sales is of outmost importance for multiple stakeholders in the pharma industry eg manufacturers distributors and regulators who rely on this data for their decisionmaking however this data is becoming increasingly biased and myopic it only accounts for drug sales from legal pharmacies overlooking sales from illegal pharmacies this limitation is becoming more and more problematic since sales from illegal pharmacies mainly operating online are growing at a substantive pace the goal of this poc is to address this limitation through the development of a web service that will provide data and business analytics on drug sales by illegal online pharmacies iops this web service will allow potential users to visualize market trends download data and develop customized reports on iops the goal of this poc is to develop a web service api that will provide data and business analytics on drug sales by illegal online pharmacies iops through a web portal this web service will allow potential users to visualize market trends download data and develop customized reports and will be provided following a payperuse commercial structure while multiple stakeholders in the pharma industry are potentially interested in this data eg manufacturers distributors pharma analytics companies policymakers and law enforcement authorities this data is currently unavailable due to the obscure nature of iops activities the web service proposed in this poc will generate such data through the algorithms designed in the illegalpharma ercfunded project accordingly this poc outlines the technological and commercial processes that will be implemented to transform the research generated in illegalpharma into a business innovation with market potential
overcoming digital divide in europe and southeast asia

digitalization has been in the epicenter of interest during the hard times of covid19 and has enabled governments and individuals to cope with the scientific and socioeconomic problems created by the pandemic both basic and advanced digital technologies as well as digital skills have been engaged to sustain the functioning of the economy and society by allowing the work to continue tracking the spread of the virus and accelerating research for medications and vaccines covid19 pandemic has shown more than anything else the utmost importance of digital assets and the need for further development towards a resilient digital transformation strengthening the digital economy and society has been one of the 6 strategic priorities of the 2021 european commission work programme with a goal of making this europes digital decade digitalization is the relevant issue in eu associated countries as well digital transformation might help eu associated countries to speed up convergence project and catch up developed eu economies even particularly topical problem is digitalization in developing countries the digital transformation and its support would lead to higher economic growth and sustainable development and the increasing of the quality of life the proposed project is as timely as ever considering the current situation of digitalization in the eu eu associated countries montenegro and developing countries in southeast asia region indonesia malaysia and thailand the focus of the project is the cooperation of the academic staff and doctoral students to engage in the research in the field of digitalization exchange their knowledge ideas and provide meaningful outputs and establish research collaboration in the field of digitalization
mapping the behavioural causes of weight change variability with genetic lottery

obesity is a heritable chronic condition costing 2 gdp worldwide many obesity treatments behavioural pharmacological and surgical have been developed intriguingly peoples responses to treatments vary widely some may lose a lot of weight whereas others may even gain weight to predict such weight change variability close to 200 measures have been proposed in the past the measures can be organised into a pebbl framework across five domains psychosocial environment behavioural biology and life quality still there are too many measures to be used as predictors or intervention targets to move the field forward we propose a novel 3step obecause pipeline consisting of consolidation genomic causation and validation 1 in consolidation we will use machine learning to find bestpredicting pebbl measures in several largescale weight loss datasets the pebbl measures will be integrated into a new pebbl short questionnaire with wide coverage and good psychometric properties the questionnaire will be then distributed to all participants of estonian biobank to study the genomics of pebbl 2 for genomic causation we will detect genetic variants behind pebbl measures and weight change knowing these variants enables discovering additions to the pebbl framework through genetic correlations and functional mapping importantly as genetic variants are randomised through genetic lottery they enable systematic causal mapping of pebbl measures that have causal effects on weight change 3 for validation these causal measures will be used as inputs to design an obecause toolbox of weight loss interventions the value of these interventions will be tested in a commercial weight loss app in summary the obecause pipeline of narrowing scattered associations down to potential causal mechanisms with machine learning and genomic causal inference will set a new standard for the behavioural health sciences allowing for quicker discovery of intervention targets
netzero selfadaptive activation of distributed selfresilient augmented services

the ambition of the natwork project is to set the foundations and deploy the very first economically realistic energy efficient and viable bioinspired aibased 6g cybersecurity and resilience framework for intelligent networking and services taking a holistic approach and considering all elements in a crosssector business environment to address the diverse requirements and challenges that arise the natwork project aims to develop a novel aileveraged selfadaptive security mechanism for 6g networks based on resilient biomimicry principles the goal is to improve the malleability and the selfresilience of future 6g network ecosystems to offer augmented and secure services at the lowest energy costs the principle premise is to empower various entities of 6g ecosystems with the ability to selfregulate their conditions to provide service continuity in compliance with service slas the secure federated learning architecture of natwork will be based on decentralized defensive ai models embedded in disaggregated 6g network physical layer smart edge network interface cards and ran devices with p4based programmable data plane and advanced dpu acceleration with local feature extraction at wirespeed and ai model training among the key 6g security challenges that natwork aims to alleviate are moving target defense and adaptive response to incidents the employment of net zero ai and energyefficient security for sustainable networks the detection of new forms of attacks bearing deep control flow monitoring as well as the elaboration of a continuum of security for payload deployment fostering secure migration of novel forms of innetwork operations and secure distributed computations
dynamics of p53 mutant reactivation and the anticarcinogenic action of engineered resveratrol analogues

the project proposal aims to engineer a bacterial host to produce variants of secondary metabolite resveratrol and address the interrelationship between dynamics structure and function of a system of high medical interest the tumor suppressor protein p53 the study considers to elucidate the mode of action of these molecules against the p53 mutants and work on new concepts for cancer therapy inside the cell the folding of a protein is a fast and robust process sometimes however sudden changes in the balance between different existing forces result in incorrect folding of the peptide chain which ends up generating amyloid aggregates within the cell that lead to the gain of toxic function since these aggregates can conduct to death of the cell in question most amyloidogenic pathologies are neurodegenerative however the aggregation also plays an important role in cancer the project provides a broad framework for the study of the resveratrol derivatives acting as p53 aggregation inhibitors by using cuttingedge tools of computational resources metabolic engineering and structural biology but could in principal be applied to exploit the chemical diversity of other biocompounds similarly intending to act as less cytotoxic agents in a more effective antineoplastic therapy which represents one of the major existing scientific gaps it is a proposal on a very important topic that will be studied from a unique perspective
towards the development of a hydrogen valley demonstrating applications in an integrated ecosystem in greece

trirs is greeces first hydrogen valley brings together business knowledge and regional interests the trirs valley starts as a small scale valley but has a tremendous upward perspective over a large part of the balkans southeastern europe and the wider area of eastern mediterranean the valley will be built around the nucleus of mohs corinth refinery complex from a business perspective the project has strong transeuropean interest as 80 of the refinery sales are generated outside of greece rendering it internationally oriented by default creating and building a valley using the refinery as hydrogen generator accelerates the transition with an annual production of 2410 tons of green hydrogen that will be utilised in the production of low and no carbon footprint energy and industrial products and will be injected in the natural gas grid creating a hydrogen backbone of full eu interest high visibility actions in mobility will include one 1 shortsea ferry ship three 3 public transport buses and at least two 2 cars knowledge and innovations are spurred through the intensive collaboration with knowledge institutes and smes the participation of the local and regional governments assures the component of public acceptance understanding and advocacy generating interest to many parties supporting regional economic growth the learnings from heavenn and wiga pg valleys will be replicated with the specific knowledge of the greek and broader connected geographies trirs entails an investment of 115 mil eur initially by project partners up to 408 million eur potential directindirect leverage of investments several thousand people will be employed during the realisation of the valley project which will promote new skills development the consortium partners are creating a true new perspective in the region transitioning from a traditional refinery complex to a stateofthe art future oriented energy and hydrogen ecosystem in the region
memoryrna the role of epitranscriptomics in thermomemory regulation

plants live in constantly changing environments and the increased frequency of extreme weather as a result of climate change will exacerbate such stresses the memoryrna project aims to expand the fundamental knowledge of nongeneticallybased regulations of the plant transcriptome during heat stress hs posttranscriptional modifications of rna create an additional layer to reversibly control rna fate the sophisticated and poorly understood thermomemory phenomenon represents a powerful system to study the role of the rna modifications and its high impact on rna metabolism to reprogram the transcriptome thus leading plants to adapt and survive to unravel the role of epitranscriptomicbased reprogramming of the transcriptome of thermomemory rnas at the shoot apical meristem the project aims to i reveal the m5c and m6a modifications transcriptomewide that actively contribute to the global cellular response to hs ii characterize the m5c and m6a marks on thermomemomery mrnas and iii determine how a m6a reader protein ect2 is regulated upon hs and its functional role on transcriptional regulation data and biological resources obtained by the team support the memoryrna project and incorporate a comprehensive set of cuttingedge technologies and approaches including i direct sequencing of longread fragments and computational analysis for accurate mapping of rna marks ii antibodybased techniques and mutant plants to validate and characterise the function of m5c and m6acontaining mrnas and iii rna and fluorescence in situ hybridization and laser confocal microscopy to investigate the role of ect2 during thermomemory understanding the mechanisms that coordinate transcriptional activity of hsmemory genes in response to environmental stressors is of utmost importance to modern agriculture and throughout the the funding period opportunities for translation of our results to biotechnological application will be monitored and explored
tungsten biocatalysis heavy metal enzymes for sustainable industrial biocatalysis

europe needs a sustainable chemical industry which will only be realized by new breakthrough technologies industrial biotechnology is established in chemical manufacturing offering more efficient more specific safer and less energy demanding production but is held back by the limited number of enzyme classes in industrial use this project opens up an important new enzyme class of tungstencontaining enzymes wenzymes which catalyse amazing chemical reactions involving challenging low redox potential reduction reactions but are currently impossible to obtain economically and on scale to match industrial needs we need to produce wenzymes using an industrial workhorse microorganism such as e coli yet we discovered that wcofactor biosynthesis is the bottleneck preventing successful production of wenzymes in e coli we can solve this challenge by using cuttingedge computational enzyme design approaches we recently developed to create a completely new wcofactor biosynthesis pathway for e coli the wbiocat strains developed in this project will enable expression of new wenzymes from genetic databases and facilitate production of new engineered wenzymes the catalytic potential of these new wenzymes will be established and implemented in new processes exciting new reaction scope in biocatalytic co2 reduction to valuable chemicals and birch reduction of aromatic compounds will be explored alongside the alreadyestablished and broadly applicable carboxylic acid reductions wbiocat will be the breakthrough to make wenzymes accessible for industry as a proof of concept a hydrogendriven process to convert plantderived oleic acid to the emollient ester oleyl oleate will be created oleyl oleate is used in many cosmetic products used daily by millions of people this process will be demonstrated in multigram yield in scalable industriallyrelevant hydrogenation reactors together with market research to address a pathway to commercialisation