This page displays news relevant to data-driven life science in Sweden, e.g. open calls and large research efforts. It will also show news related to the SciLifeLab Data Platform. For example, we will announce updates on the tools, services, and databases on the SciLifeLab Data Platform.
Request for descriptions of proposed national data services related to Cell and Molecular Biology
SciLifeLab collaborates with specific partner orgnanisations to organise work related to data services and bioinformatics support as part of the The SciLifeLab and Wallenberg National Program for Data-Driven Life Science (DDLS). This work takes place at one of four Data Science Nodes. These four nodes, one for each of the scientific focus areas of the DDLS program, are located across Sweden. They comprise of staff from SciLifeLab Data Centre and NBIS (National Bioinformatics Infrastructure Sweden). The staff are embedded in relevant environments at the hosting organisations, and are also integrated in the national data platform and bioinformatics support teams, respectively.
The aim of the SciLifeLab Data Platform is to boost the number of services available for data-driven life science research in Sweden. The aim of the SciLifeLab Data Platform is to create an envronment in which users can easily locate, access, and use resources (including data, tools, and e-infrastructure) relevant to data-driven life science research. Each of the Data Science Nodes works with the SciLifeLab Data Platform towards this aim.
The Cell and Molecular Biology Node (hosted at Chalmers University of Technology) is reaching out to the data-driven life science community for descriptions of potential national data services in the field of cell and molecular biology. These services will then be assessed for inclusion in the SciLifeLab Data Platform. The services will benefit from, among other things, significantly increased promotion, which could lead to greater opportunities for funding opportunities and collaboration.
To find out more about the application process and requirements, please see the Cell and Molecular Biology National Data Services request document.
List of data sources available for researchers
A new resource entitled ‘Data Sources’ has been added to the SciLifeLab Data Platform. The resource lists sources of data that can be used by data-driven life science researchers in Sweden. We are looking for feedback from the community about how this resource might be improved in future, and encourage users to get in touch with us about any suggestions.
The list includes entries where data can be both deposited and downloaded (termed ‘repositories’), and those where data can just be accessed (termed ‘data sources’). Users can search for particular entries by their name or keywords (allowing for more granularity), and can also filter the list according to a particular type of data (e.g. protein data, phylogenetic data) and/or scientific area. The list currently contains over 80 entries, and will be expanded over time.
New data highlight exploring a new metagenomic profiling workflow for ancient DNA
A new data highlight entitled ‘aMeta: a new metagenomic profiling workflow for ancient DNA’ explores a new metagenomic profiling workflow for ancient DNA. It is based on work recently published in Genome Biology by Pochon et al. (2023).
The development of technologies that can be used to study ancient DNA (aDNA) have led to many recent discoveries that allow us a clearer picture of the ancient past. Studies of microbial DNA from archeological samples, and sedimentary ancient DNA (sedaDNA) represent rapidly growing areas of research. However, there remain some limitations in what is possible with aDNA studies. For example, when studying ancient microbial DNA, there are typically high rates of false-positives and false-negatives for the presence of ancient microbial DNA. More stringent ancient metagenomic computational workflows could help to reduce the error rate, but few are available. AMeta represents a new workflow that has been shown to be superior to the current standard.
See the data highlight for more details: aMeta: a new metagenomic profiling workflow for ancient DNA. Relevant data highlights will be shown at the bottom of the page. To get your work featured as a data highlight, please get in touch with us to discuss it.
New data highlight exploring alterations to the serum proteome caused by COVID-19
One of two data highlights published today details a meta-analysis of alterations in the soluble blood proteome caused by COVID-19. It is entitled ‘CoViMAPP – analysing changes in the soluble blood proteome due to COVID-19’. It is based on work recently published in Nature. Please see Babačić et al. (2023) for the original open-access article.
Many studies have investigated how compounds in blood serum are affected by COVID-19, though proteins remain the most frequently used in clinical practice. Despite this, only a relatively small portion of the proteome has been explored to date, and coverage is very low. Babačić et al. (2023) used multiple methods to expand the coverage of the proteome. Their study comprised of meta-analysis inlcuding both known mass spectrometry datasets and a dataset that they generated during their own investigations. The researchers have placed their findings in an app, named CoViMAPP, that can be used as a dynamic tool for future meta-analyses.
To read more, check out the data highlight: CoViMAPP – analysing changes in the soluble blood proteome due to COVID-19. Other data highlights on similar topics will also be visible at the bottom of the article.
If you’d like to get your work featured as a data highlight, please get in touch with us to discuss it.
New highlight explores expansion of Bantu-speaking populations
One of two data highlights published today explores the expansion of Bantu-speaking populations. It is entitled ‘New DNA research into Bantu-speaking populations’ expansion provides a resource for future studies’. It is based on work recently published in Nature, please see Fortes-Lima et al. (2023) for the original open-access article.
Around one-third of people in Africa speak at least one Bantu language (of which there are over 500). The expansion of people speaking one of these languages is considered one of the most dramatic events in late-Holocene Africa. The work done by Fortes-Lima et al. (2023) is the first to suggest a serial-founder migration model. This was achieved using more up-to-date genetic methods and modeling approaches than in previous studies. The authors have created a new genetic dataset, called ‘AfricanNeo’, which is a valuable resource for multiple disciplines, including health, medicine, and humanities. They have made the code used for creating their plots avaiable for reuse.
To read more, check out the data highlight: New DNA research into Bantu-speaking populations’ expansion provides a resource for future studies. Other data highlights on similar topics will also be visible at the bottom of the article.
If you’d like to get your work featured as a data highlight, please get in touch with us to discuss it.
Multiple open source services added
We have recently added multiple open source tools to our services list. We define services as tools, databases, and support services (e.g. hosting and compute services) that can be used in data-driven life science research. Whilst we list services associated with SciLifeLab, the services can be used anywhere in the world, free of charge, unless otherwise stated.
The newly listed services are primarily tools for use with sequence data. For example, Cutadapt detects and removes unwanted sequences from high-throughput sequencing reads, and CheckQC checks a set of quality control criteria against an Illumina reader. Other newly listed services include Chanjo (a sequencing coverage assessment tool), nf-core/Sarek (a workflow designed to detect variants), GENMOD (a tool to annotate and analyse genomic variants), and MultiQC (a tool that aggregates the results of bioinformatics analyses across many samples). We have also added nf-core to our services list. Nf-core is a community effort to collect a set of analysis pipelines and modules built using Nextflow. Whilst some of the pipelines and modules listed on nf-core are designed for work with sequence data (e.g. nf-core/Sarek), many are instead intended for use with other types of data.
We will continue to list new services over time. If you are aware of a revelant service that is not listed, please get in touch with us. We will review any suggestions as soon as possible, and promptly list relevant services.
If you are instead interested in learning more about a particular area, then please check out our resources section. Our resources are collections of information on a given topic. Fir example, we have resources related to the compute and storage resources available for use with data-driven life science in Sweden.
New highlight details a workflow that could aid in future drug development
Our latest data highlight, entitled ‘research into the immunogenicity of GPCR epitopes to enhance future drug development’, is based on Dahl et al. (2023).
Proteins in the GPCR superfamily (heterotrimeric guanine-nucleotide-binding regulatory protein (G protein)–coupled receptors) are important in normal cellular physiology and intercellular communication. GPCRs are linked to multiple diseases and are the targets of many therapeutic drugs. Indeed, recently, biological drugs have been introduced that modulate GPCR function based on the binding of anti-GPCR antibodies. However, challenges remain with developing drugs based on GPCRs; there is high sequence similarity between GCPRs in the same subfamily, and anti-GPCR antibodies are crucial reagents in studies of GPCR biology and pharmacology. Dahl et al. (2023) developed a workflow to investigate GPCR immunogenicity. They have openly shared the data generated and created an R Shiny app to enable others to browse their data.
Read more in the Data Highlight: Research into the immunogenicity of GPCR epitopes to enhance future drug development. You’ll also see other highlights on related topics at the bottom of the article.
Do you have some data-driven life science research that you’d like to highlight, or even present as a service, on the SciLifeLab Data Platform? If so, please fill out the forms on the appropriate pages or get in touch with us.
SciLifeLab FAIR Storage
SciLifeLab FAIR Storage has now been added as our latest service. SciLifeLab FAIR Storage is a service providing storage resources to enable FAIR data sharing within Swedish data-driven life science. The applications and allocation of resources will be managed by SciLifeLab Data Centre.
Documents related to the use and application of the resource can be found at the SciLifeLab FAIR Storage service page. More guidelines and information will be added to the page as it becomes available.
There will be an event aimed at explaining how to apply to use FAIR Storage resources on November 30th 10:00 – 11:30 (CET). There will also be a call open through the Swedish User and Project Repository (SUPR) Portal (call open Nov 16th - Dec 31st). If you’d like to reach out with any questions directly, you can do so using the contact information for the service shown on our services page. In this case, you can send an email to FAIRstorage@scilifelab.se.
New resource on using alternative metrics
We have now launched our third resource, which is focused on how to use alternative metrics. In particular, the resource describes what altmetrics are, why they’re important for researchers, how to use them, and how to maximise your score. The resources have now been made accessible directly on the front page of the platform. As you’ll see, the other resources detail the compute and storage resources in Sweden, and how to access them.
If you are interested in finding out more about any of the topics listed in resources, or have ideas for additional resources, please contact us with your suggestion.
New highlight details a large study investigating the initiation of replication in E. coli.
Our latest data highlight, entitled: Large effort study to elucidate replication initiation in bacteria, is based on Knöppel et al. (2023).
Over the last 50 years, the research community has studied the coordination of DNA copying and cell division in bacteria. The studies completed have shown that a protein called DnaA is key in the replication of Escherichia coli. Recent studies have made use of microscropy in order to advance our understanding of E. coli replication processes, but much is still unknown. Knöppel et al. used high-throughput fluorescence microscopy to study the coordination of replction and division cycles in E. coli. Their results supported the initiator activation/deactivation cycling model for E. coli replication initiation, but the researchers advocate for further studies into this model.
Read more in the Data Highlight: Large effort study to elucidate replication initiation in bacteria. You’ll also see other highlights on related topics at the bottom of the article.
Do you have some data-driven life science research that you’d like to highlight, or even present as a service, on the SciLifeLab Data Platform? If so, please fill out the forms on the appropriate pages or get in touch with us.
Information about accessing storage resources added
We have now added a second resource to our new resources section. This resource details the storage resources available in Sweden and how to access them. These resources can be used to store data and potentially other types of resources. This latest page is considered a compliment to our compute resources page, which provides information about resources related to analysis and hosting.
If you are interested in finding out more about compute and storage resources, please join our Overview of compute and storage resources in data-driven life science event tomorrow (8th September 2023). A recording will be made available after the event.
If you have questions related to compute and storage resources in Sweden, or comments about our resources pages, please contact us.
Launch of resources section
We are delighted to announce the launch of our new resources section. The aim of this section is to provide general information that could be of use for those working in data-driven life sciences in Sweden. This section currently includes introductory information about computing resources available in Sweden. In the coming months, we will also add information about storage resources available in Sweden, and how researchers can maximise their Altmetrics score. If you have any suggestions for other information that could be useful for data-driven life science in Sweden, please get in touch.
Our services section enables direct access to tools, datasets, and support functions (e.g. hosting services) available for use in data-driven life science in Sweden. Our new resources section differs because it is for information, rather than a specific service itself. However, the team at SciLifeLab Data Centre are happy to provide further support on the areas considered in this section, so please contact us with any questions.
This new section was initially introduced at our launch event back in May (the recording from the launch event is available at DOI:10.17044/scilifelab.23266088).
Glad sommar!
The team behind the SciLifeLab Data Platform wish you all a wonderful summer break. There will be limited support for the Platform throughout July, but if you get in touch, we will reply to you ASAP!
New highlight shows how changes in METTL3 localisation could hold the key to new antiviral strategies against SARS-CoV-2.
We have published a new data highlight, entitled: METTL3 localisation during SARS-CoV-2 infection could highlight new novel antiviral strategy, which is based on Vaid and Mendez et al. (2023).
The recent COVID-19 pandemic has highlighted the importance of finding novel routes for treatment in minimising the negative effect of infectious diseases on society. The N6-Methyladenosine modification (m6A) is one of the most common cellular RNA modifications, and known to play a crucial role in the regulation of RNA metabolism during the stress response. Vaid and Mendez et al investigated changes in m6A expression during SARS-CoV-2 infection to determine whether this could be the key to novel or improved antiviral therapeutics for SARS-CoV-2. They found that SARS-CoV-2 infection caused a loss of m6A in cellular RNAs. This was related to partial relocalisation of the methyltransferase METTL3/METTL14 complex from the nucleus to the cytoplasm. Both sequencing data and analysis code from this study are shared.
Read more in the Data Highlight: METTL3 localisation during SARS-CoV-2 infection could highlight new novel antiviral strategy. You’ll also see other highlights on related topics at the bottom of the article.
Do you have some data-driven life science research that you’d like to highlight, or even present as a service, on the SciLifeLab Data Platform? If so, please fill out the forms on the appropriate pages or get in touch with us.
New services and SciLifeLab Data Platform Launch materials now available
Thank you to all of those that were able to join us for the official launch of the SciLifeLab Data Platform on 26th May. For those who missed it, the recording is now available via the SciLifeLab Data Repository (one of the services on the SciLifeLab Data Platform). You can access it at: DOI: 10.17044/scilifelab.23266088.
We also added some new services to the Platform ahead of the launch. These include:
More services will be added soon. Please see our services page in order to explore all of the services available on the SciLifeLab Data Platform.
If you want to stay up to date with future events related to data-driven life science in Sweden, make sure to check our events page regularly!
New highlight shows variability in IGH antibody genes influences the response to SARS-CoV-2.
We have published a new data highlight, entitled: Variability in IGH antibody genes influences the response to SARS-CoV-2, which is based on Pushparaj et al. (2023).
The pandemic has highlighted the importance of research into our ability to control infections and interindividual response to disease and vaccination. While some genes have been found to be connected with protective effects against SARS-CoV-2, others have been connected with increased risk to develop severe disease. The immunoglobulin heavy-chain IGHV1-69 gene is highly polymorphic and as such likely to have implications for the human response to infection, and vaccination. In their study Pradeepa Pushparaj and colleagues from Karolinska Institutet (Corresponding author: Gunilla B Karlsson Hedestam) studied the role of IGH germline gene variation in antibody response against SARS-CoV-2. The researchers showed that human IGH antibody genes are highly variable and germline-encoded residues specific to given IGHV1-69 alleles can shape the neutralizing antibody response to SARS-CoV-2. This means that genetic differences can influence our antibody response to SARS-CoV-2 and shape long-lived memory B cell responses induced by infection or vaccination. Both data and the IgDiscover software are openly shared.
Do you have some data-driven life science research that you’d like to highlight, or even present as a service, on the SciLifeLab Data Platform? If so, please fill out the forms on the appropriate pages or get in touch with us.
New services launched related to compute resources
We have added two new services pages that are designed to aid researchers, research groups, and research infrastructure to make use of compute resources (otherwise known as e-infrastructure).
The first new service is related to hosting on the SciLifeLab Data Platform’s technical environment. Scilifelab provides e-infrastructure services complementing those available from national e-infrastructures, and with a focus on resources for FAIR data sharing. This includes compute- and storage resources for hosted services adhering to principles of FAIR and Open Science. For more information, and to learn how to apply, please see the page on ‘hosting on the SciLifeLab Data Platform.
The second new service is a compilation of information related to compute resources available in Sweden. This is designed to improve awareness of the e-infrastructure available in Sweden. On that page, we have also include information on how to apply for access.
We will continue to expand on these services in future. We welcome and suggestions for additions or potential clarifications. Please feel free to get in touch with us.
Launch of the SciLifeLab Data Platform
Please join us for the official launch of the Platform - May 26th at 11am via Zoom!
At this launch event, we will demonstrate how the data platform supports data-diven life science, the services we offer, and how you can get access to hosting resources. In addition, a number of our users will present their user cases, followed by a summary.
To find out more about this and other events related to data-driven life science in Sweden, see our events page!
New highlight defining a new concept in antibiotic resistance - antibiotic perseverance
We have published a new data highlight, entitled ‘New study shows that perserverance can be the reason for antibiotic resistance development’, which is based on Brandis et al. (2023)
Antibiotic resistance is often termed the ‘silent pandemic’. As resistance to antibiotics becomes more widespread, it is becoming clearer that there may be a day where currently curable diseases are no longer easily treatable with antiobiotics. In a recent publication, researchers systematically exposed Escherichia coli to above-MIC (minimal inhibitory concentration) or sub-MIC concentrations of antibiotics in order to study the development of resistance.As a result of this work, the researchers described a new concept; antibiotic perseverance. They defined antibiotic perseverance as the ability of a subpopulation to maintain replication longer than the main population even at the MIC. Antibiotic perseverance was found to be a common phenomenon that increased the risk of the development of resistance by up to 40-fold in both gram-negative and gram-positive species. Raw microscopy image data and code used for analysis are both openly shared.
Do you have some data-driven life science research that you’d like to highlight, or even present as a service, on the SciLifeLab Data Platform? If so, please fill out the forms on the appropriate pages or get in touch.
New DDLS Strategy launched
The strategy for the SciLifeLab and Wallenberg Netional Program for Data-Driven Life Science (DDLS) has been updated. The corresponding strategy document is now publicly available.
It is clear that the future of science is becoming increasingly data driven, with the quantity and complexity of data seemingly ever-increasing. To meet the new challenges arising from this, the scientific community must gain more data analysis expertise and develop new capabilities. The DDLS encapsulates this in it’s vision ‘The future is data-driven’, and aims to equip the life science community of Sweden with the necessary skills and capabilities to enable them to thrive in this new scientific age.
The DDLS program was funded in late 2020 by the Knut and Alice Wallenberg Foundation (KAW), and is hosted primarily by SciLifeLab. It is a 12 year, 3.1 Billion SEK program. The program will recruit 39 DDLS fellows, 250 PhD students, and around 200 Postdocs.
This new long-term strategy reflects the plans for the next 10 years of the program. It was developed by the DDLS steering group, the eleven participating organisations (ten universities, Chalmers, GU, KI, KTH, LiU, LU, NRM, SLU, SU, UmU and UU, and the Swedish Museum of Natural History, NRM), as well as the SciLifeLab Board, SciLifeLab International Advisory Board (IAB), SciLifeLab Management Group, SciLifeLab Operations Office, SciLifeLab Data Centre, NBIS, and in communication with other KAW-funded research programs. Please see the official news release from Scilifelab for more.
Get your work featured!
It is now easier than ever to get your work featured on the SciLifeLab Data Platform. All you have to do is get in touch to tell us about what you’d like to share/have hosted, so that we can begin the review process.
We offer hosting for services related to data-driven life science in Sweden, and are happy to include services hosted elsewhere in our Service catalogue. We also publish short, data-focused articles (data highlights) to promote research that shares data and/or code in accordance with the principles of FAIR and open data sharing.
We update jobs, calls, and events/training opportunities on the site weekly, and are happy to hear about opportunities that you’d like promoted within the Swedish data-driven life science community.
New highlight on study revealing sex determination genes in a malaria parasite that are essential in disease transmission
We have published a new data highlight, entitled ‘Discovery of sex determination genes in a malaria parasite that are essential for mosquito transmission’, which is based on Russell et al. (2023)
Malaria remains a major threat to public health. Understanding how malaria is transmitted via mosquitoes is crucial in tackling the spread of the disease, because it could enable scientists to devise new methods of preventing the spread. In a recent publication resulting from an international collaboration, reserachers studied how sex is determined in Plasmodium berghei, and how this affects transmission of malaria. Plasmodium berghei is a causative agent of malaria in rodents, and can be used as a model to study malaria in humans. The researchers combined functional screens of barcoded mutants and single cell transcriptomics to understand the biology of this highly divergent and poorly tractable eukaryote. Raw data, as well as mass spectrometry data and code were shared openly.
Do you have some data-driven life science research that you’d like to highlight, or even present as a service, on the SciLifeLab Data Platform? If so, please fill out the forms on the appropriate pages or get in touch.
Making it easier to find job/funding/project opportunities in data-driven life science.
You may have become familiar with our ‘Calls & Jobs’ section over the last few months. The section included funding calls, jobs, postdoc positions, PhD positions, and project opportunities related to data-driven life science. We’re now making it easier for you to find exactly what you’re looking for!
We’ve split ‘Calls & Jobs’ into two sections; ‘Jobs’ and ‘Funding calls’. In the Jobs section, you’ll find postdoc positions, BSc/MSc project opportunities, and other jobs in data-driven life science. Anyone that wants to promote a relevant position on the page is welcome to use the form on that page to get in touch (alternatively, you can email data-platform@scilifelab.se or datacentre@scilifelab.se). In the Funding calls section, you’ll find direct links to funding opportunties from SciLifeLab, and potential other sources of funding for data-driven life science projects.
We’ve also added filtering to the Jobs section. This allows you to search for a given type of position (job/postdoc position/PhD position/project opportunity), and/or for positions with a given employer.
These sections are updated weekly (usually on Fridays), so it’s worth checking back regularly for new opportunities!
If you have any suggestions for improvements that can be made to any element of the SciLifeLab Data Platform, or recommendations for new sections/services that could be added, please get in touch.
New data highlight related to the use of a long-read sequencing method in cancer diagnostics
We have published a new data highlight, entitled ‘Novel long-read sequencing workflow developed for use in routine cancer diagnostics’, which is based on Schaal et al. (2022).
Some patients develop resitance to drugs used to treat Chronic Myeloid Leukemia (CML). Sanger sequencing is routinely used in clinical settings to identify mutations related to this drug resistance. Sanger sequencing has known limitations, but is used as routine due to difficulties in establishing newer methods in a clinical setting. Schaal et al. (2022) developed a workflow/pipeline that makes use of long-read sequencing, which was recently named Method of the Year 2022 by Nature Methods, to detect and identify mutations related to drug resistance in Chronic Myeloid Leukemia (CML) treatment. The showed that this pipeline was both more senstive than Sanger sequencing, and relatively simple to establish in clinical settings.
Do you have some data-driven life science research that you’d like to highlight on the SciLifeLab Data Platform? Or perhaps you have events/jobs/projects in your group that you’d like to advertise on the SciLifeLab data platform? If so, please fill out the forms on the appropriate pages (e.g. in the data highlights section), or email us at datacentre@scilifelab.se.
Happy holidays to all (see you in the new year)!
We on the SciLifeLab Data Platform would like to take this opportunity to to wish you all ‘God jul och gott nytt år!’. We’d also like to thank the data-driven life science community in Sweden for their support in our very first year! We’ve developed some great collaborations with the community this year, and look forward to continuing those (and building even more!) next year.
The team are also getting into the spirit, and support levels will be lower during the holiday period. We’ll be back to normal levels of support from 9th January 2023.
In the meantime, please feel free to get in touch with us, and we’ll get back to you as quickly as you can! We’re always really happy to hear about any jobs, funding, or project opportunities, potential data highlights, or events that could be of interest to the data-driven life science community.
New data highlight related to the study of enteroviruses
We have published a new data highlight, entitled ‘Cryo-electron tomography allows new knowledge about poliovirus replication and assembly sites in situ’, which is based on Dahmane et al. (2022). The study used cryo-electron tomography to examine how enteroviruses are assembled and packaged into autophagosomes. Enteroviruses cause many diseases, some of which can have devastating effects on society, such as polio. The data and code related to the study are openly shared to support the reproduction of the results of the present study, as well as future studies in this area. This highlight is also published on the COVID-19 and Pandemic Preparedness Portal, as it relates to pandemic preparedness work.
Do you have some data-driven life science research that you’d like to highlight on the SciLifeLab Data Platform? Or perhaps you have events/jobs/projects in your group that you’d like to advertise on the SciLifeLab data platform? If so, please fill out the forms on the appropriate pages (e.g. in the data highlights section), or email us at datacentre@scilifelab.se.
Improving user experience and Data Science Node (DSN) jobs
We’ve made multiple changes to the Data Platform aimed at improving user experience. In particular, we’ve made changes to the homepage layout, adjusted the colour and size of some elements (e.g. services cards, hyperlinks) to make them clearer, and made it possible to link directly to different data higlights and services by clicking on the images associated with them. We’d be interested to hear any feedback that you might have for further improvements that we should consider.
Today, we are also releasing our largest single update of jobs to date. Many of the jobs in this update are related to the establishment of Data Science Nodes (DSNs) that are being established as part of the SciLifeLab and Wallenberg National Program for Data-Driven Life Science (DDLS). Our jobs page is updated weekly, so we encourage those looking for positions in the area of Data-Driven Life Science to check back regularly! Those advertising a position in this area are invited to inform us of it by filling in the form on our jobs page.
We will continue to add new events, data highlights, and services as they become available. Please get in touch if you’re interested in advertising an event on the Data Platform, or if you’re interested in having your research become the subject of a data highlight.
New data highlight added, and other updates
Our latest data highlight, entitled ‘New study shows crossing the salt barrier has shaped the diversity of life’ is based on Jamy et al. (2022). The study examines the evolution of habitat preference across eukaryotes. Specifically, they considered transitions across the ‘salt-barrier’. Their study showed that such transitions were likely key evolutionary events that were integral to creating the eukaryotic diversity we see today. This data highlight was a contribution direct from the life science community, and was written by first author Mahwash Jamy. As with all of our data highlights, the resources from the project are shared as openly as possible and are directly linked in the highlight to improve findability.
We have also been making regular updates to our jobs and events pages. Please check those out to stay up to date on the latest opportunities relevant to data driven life science.
Do you have some data-driven life science research that you’d like to highlight on the portal? Or perhaps you have events/jobs/projects in your group that you’d like to advertise on the SciLifeLab data platform? If so, please fill out the forms on the appropriate pages (e.g. in the data highlights section), or email us at datacentre@scilifelab.se.
New data highlight 'GenErode pipeline can compare patterns of genomic erosion using genomic data from historical, ancient and modern samples' added.
Today, we have published a new data highlight on the SciLifeLab Data Platform. This latest highlight, details work on the GenErode pipeline as described in a recent paper by Kutschera et al. (2022). The GenErode pipeline is the first bioinformatics pipeline that can process and analyse ancient, historical, and modern sequencing data from the same species with the aim of generating comparable estimates of genomic erosion indices. Experience with coding with not necessary to work with this pipeline, and all bioinformatics steps are well documented, making it very accessible to users.
Have you completed some data-driven life science research and openly shared the data and/or code? Why not get in touch about having it featured as a data highlight? You can contact us by completing the form in our data highlights section, or emailing us at datacentre@scilifelab.se.
New data highlight 'Bayesian deep learning model finds clues about the evolution of open habitats' added.
Our latest data highlight is now live on the SciLifeLab Data Platform. This latest highlight, summarises a recent paper by Andermann et al. (2022). The study explores the evolution and expansion of open grassland habitats. The study uses deep learning models that are trained using information on mammal-plant interactions based on openly available fossil record data.
Have you completed some data-driven life science research and openly shared the data and/or code? Why not get in touch about having it featured as a data highlight? You can contact us by completing the form in our data highlights section, or emailing us at datacentre@scilifelab.se.
New service related to the subcellular localisation of proteins and the outcomes of the SubCellBarCode project.
Today, we have launched a new service page related to the SubCellBarCode project. The SubCellBarCode service page is a collation of all of the resources (including tools, web portal, publications, methodologies, etc.) produced as part of the SubCellBarCode project. This page has been produced in close collaboration with those involved in the project and will be updated with new outcomes over time.
The aim of this service page is to facilitate the use of the tools and resources generated within the SubCellBarCode project. The project has shared a significant amount of data, in-depth explanations regarding the methodologies used, and multiple research tools (e.g. R analysis package, visualisation tools). Each of these elements can be accessed from the SubCellBarCode service page. It is hoped that the collation and promotion of these resources will accelerate efforts related to the subcellular localisation of proteins. Such studies are incredibly important, particularly as they have implications in human disease e.g. in cancer.
If you have a tool/dataset/service/set of resources that you think that we should add to our service catalogue, reach out to let us know!
New service related to the management of life science research data in Sweden
We are pleased to announce the launch of SciLifeLab RDM (research data management) guidelines. This new resource, developed and maintained in collaboration with NBIS, will act as a knowledge hub for the management of life science research data in Sweden. The resource will be updated and expanded over time, with new features and sections already planned. As always, we encourage you to get in touch with any feedback that you might have on this new service.
If you have a tool/dataset/service/set of resources that you think should be added to our service catalogue, please let us know!
New feature added - Recent apps deployed on SciLifeLab Serve displayed on homepage
We have added a new feature that is related to one of our services; SciLifeLab Serve. SciLifeLab Serve is a service for deploying apps (including Shiny and Dash apps) and serving machine learning models (Tensorflow and PyTorch serving). The service is currently in beta testing and is looking for test users.
You will find the 8 most recently deployed public apps at the bottom of the homepage on the SciLifeLab Data Platform. You can click on the app title to go directly to a specific app. Alternatively, you can go straight to SciLifeLab Serve itself to explore more public apps and models, as well as find out how to enquire about becoming a test user.
New data highlight 'DNA methylation inherited across generations in water fleas may influence freshwater ecosystems' added.
We’re starting off the post-summer season on the SciLifeLab Data Platform with a new data highlight. This latest highlight, summarises a recent paper by Feiner et al. (2022). The study explored whether epigenetic effects, induced by stressors, could influence freshwater ecosystems long-term. The study focussed in particular on the impact that climate change could have on this threatened ecosystem type.
Have you completed some data-driven life science research and openly shared the data and/or code? Why not get in touch about having it featured as a data highlight? You can contact us by completing the form in our data highlights section, or emailing us at datacentre@scilifelab.se.
New data highlight 'Unravelling the assembly of the mitoribosome' added
Check out the latest data highlight added to the SciLifeLab Data Platform. This highlight, entitled ‘Unravelling the assembly of the mitoribosome’, relates to a recent publication by Itoh et al. (2022). The study uses cryo-electron microscopy to understand the mechanisms underlying mitoribosomal assembly.
It is the first data highlight to be drafted by one of the corresponding authors of the original paper - in this case, senior author Prof. Alexey Amunts. If you’re interested in writing a data highlight to promote data-driven life science research that you’ve been involved in, please complete the form in our data highlights section, or email us at datacentre@scilifelab.se.
New data highlight 'A deep learning framework to estimate species diversity' added
A new data highlight has been added to the SciLifeLab Data Platform. This latest data highlight, entitled ‘A deep learning framework to estimate species diversity’ considers a recent publication by Andermann et al. (2022). The study explores whether deep learning frameworks can be used to accurately estimate biodiversity, and thus to target conservation efforts.
All of our data highlights can be found in our data highlights section. Why not check out our other highlights too?
Want to suggest a study for us to highlight? Get in touch by filling in the form in our data highlights section, or email us at datacentre@scilifelab.se.
New section on calls/jobs/projects related to data-driven life science in Sweden
A new section has been added to the SciLifeLab Data Platform. In our new ‘Calls & Jobs section’, we will show all of the latest funding calls, job listings, and masters thesis opportunities related to data-driven life science in Sweden. You will be able to see the application deadline, location, and basic summary information right on the page. We’ll also provide a link to where you can find out more.
See something we’ve missed? Feel free to get in touch with us to make suggestions for how to improve the page, or to tell us about opportunties that you think should be listed.
SciLifeLab Data Platform website launched
Today marks the official launch of the SciLifeLab Data Platform website, which can be found at data.scilifelab.se. The Platform will act as a hub for data-driven life science in Sweden. It will include work on data-driven life science from all those affiliated with a Swedish research institution, not just SciLifeLab. The Platform will incorporate multiple resources (tools, services, and datasets), and highlight relevant news, data, and events. Much more will be added over time, so watch this space.
We invite the the research community to contribute to all sections of the Platform. We welcome their feedback on the current content, as well as their suggestions on what else they would like to see here.
SciLifeLab Data Centre to lead work on databases and data support for DDLS
In a recent meeting, the SciLifeLab Board assigned SciLifeLab Data Centre to lead work on databases and data support for the Wallenberg National Program on Data-Driven Life Science (DDLS). SciLifeLab Data Centre will report on this work to the DDLS steering group. A budget of 140 MSEK has been allocated for the support of databases and data support during the first three years of the program.
Wallenberg National Program on Data-Driven Life Science (DDLS) announced
The Knut and Alice Wallenberg foundation has announced the Data-Driven Life Science (DDLS) program. Funding for the program comprises 3.1 billion SEK, to be distributed over a period of 12 years. The initiative gives priority to data-driven life science in 4 areas; cellular and molecular biology, evolution and biodiversity, precision medicine and diagnostics, and epidemiology and infection biology.