36 Works

Conformal Prediction in Learning Under Privileged Information Paradigm with Applications in Drug Discovery

Ola Spjuth, Niharika Gauraha & Lars Carlsson
Presentation held by Niharika Gauraha at the conference "Conformal Prediction and Probabilistic Predictions with Applicationsi (COPA) 2018".

Conformal Prediction in Learning Under Privileged Information Paradigm with Applications in Drug Discovery

Ola Spjuth, Niharika Gauraha & Lars Carlsson
Presentation held by Niharika Gauraha at the conference "Conformal Prediction and Probabilistic Predictions with Applicationsi (COPA) 2018".

Predictive Models For Off-Target Binding Profiles Generation

Samuel Lampa, Jonathan Alvarsson, Staffan Arvidsson Mc Shane, Arvid Berg, Ernst Ahlberg & Ola Spjuth
Models for predicting off-target binding, built with Conformal Prediction, and the CPSign software. The dataset is part of an upcoming publication (Manuscript in preparation), which will provide more details. The dataset is a GZipped Tar archive, with the models as Java Archive (JAR) files. For every JAR-file, there is also a corresponding audit log, with the extension ".audit.json", produced by the workflow software (SciPipe) used to train the models. This audit file contains all the...

Predictive Models For Off-Target Binding Profiles Generation

Samuel Lampa, Jonathan Alvarsson, Staffan Arvidsson Mc Shane, Arvid Berg, Ernst Ahlberg & Ola Spjuth
Models for predicting off-target binding, built with Conformal Prediction, and the CPSign software. The dataset is part of an upcoming publication (Manuscript in preparation), which will provide more details. The dataset is a GZipped Tar archive, with the models as Java Archive (JAR) files. For every JAR-file, there is also a corresponding audit log, with the extension ".audit.json", produced by the workflow software (SciPipe) used to train the models. This audit file contains all the...

Supporting data for "Tracking the NGS revolution: managing life science research on shared high-performance computing clusters"

Scofield Douglas, Dahlö Martin, Spjuth Ola & Schaal Wesley
Next-Generation Sequencing (NGS) has transformed the life sciences and many research groups are newly dependent upon computer clusters to store and analyse large datasets. This creates challenges for e-infrastructures accustomed to hosting computationally mature research in other sciences. Using data gathered from our own clusters at UPPMAX computing centre at Uppsala University, Sweden, where core hours usage by ∼800 NGS and ∼200 non-NGS projects is now similar, we compare and contrast the growth, administrative burden...

The future of metabolomics in ELIXIR.

Merlijn Van Rijswijk, Charlie Beirnaert, Christophe Caron, Marta Cascante, Victoria Dominguez, Warwick B Dunn, , Franck Giacomoni, Alejandra Gonzalez-Beltran, Thomas Hankemeier, Kenneth Haug, Jose L Izquierdo-Garcia, Rafael C Jimenez, Fabien Jourdan, Namrata Kale, Maria I Klapa, Oliver Kohlbacher, Kairi Koort, Kim Kultima, Gildas Le Corguillé, Pablo Moreno, Nicholas K Moschonas, Steffen Neumann, Claire O'Donovan, Martin Reczko … & Christoph Steinbeck

Rdf Dataset For Article: A Confidence Predictor For Logd Using Conformal Regression And A Support-Vector Machine

Maris Lapins, Staffan Arvidsson, Samuel Lampa, Arvid Berg, Wesley Schaal, Jonathan Alvarsson & Ola Spjuth
RDF dataset described in article: "A confidence predictor for logD using conformal regression and a support-vector machine" (Manuscript in preparation). The dataset contains conformal logD values at 90% confidence level, computed for 91M compounds from PubChem, in RDF format. The .hdt.gz version contains the dataset in RDF HDT format (http://www.rdfhdt.org/), compressed with tar and gzip. The archive contains both the .hdt file, and an index file, generated by the hdtSearch C++ tool. The .ttl.gz file...

Rdf Dataset: A Confidence Predictor For Logd Using Conformal Regression And A Support-Vector Machine

Maris Lapins, Staffan Arvidsson, Samuel Lampa, Arvid Berg, Wesley Schaal, Jonathan Alvarsson & Ola Spjuth
RDF version of the cpLogD dataset. The .hdt.gz version contains the dataset in RDF HDT format (http://www.rdfhdt.org/), compressed with tar and gzip. The archive contains both the .hdt file, and an index file, generated by the hdtSearch C++ tool. The .ttl.gz file is a gzipped file in RDF Turtle format (https://www.w3.org/TR/turtle/).

Rdf Dataset: A Confidence Predictor For Logd Using Conformal Regression And A Support-Vector Machine

Maris Lapins, Staffan Arvidsson, Samuel Lampa, Arvid Berg, Wesley Schaal, Jonathan Alvarsson & Ola Spjuth
RDF version of the cpLogD dataset. The .hdt.gz version contains the dataset in RDF HDT format (http://www.rdfhdt.org/), compressed with tar and gzip. The archive contains both the .hdt file, and an index file, generated by the hdtSearch C++ tool. The .ttl.gz file is a gzipped file in RDF Turtle format (https://www.w3.org/TR/turtle/).

RDFIO (3.0.2) Demo Virtual Machine

Samuel Lampa, Egon Willighagen, Pekka Kohonen, ALISON KING, Denny Vrandečić, Roland Grafström & Ola Spjuth
A virtual machine demonstrating the RDFIO extension [1] for for enabling import, export and SPARQL querying in Semantic MediaWiki [2] wikis, as recently published in [3]. The script to generate this virtual machine is available in [4].
Instructions
1. Download the .ova file2. Import the .ova file in a virtual machine player like VirtualBox of VMWare3. Start the virtual machine4. Log in as Ubuntu (no password required, but it is "changethis..." if you need it)5. Highly recommended...

RDFIO (3.0.2) Demo Virtual Machine

Samuel Lampa, Egon Willighagen, Pekka Kohonen, ALISON KING, Denny Vrandečić, Roland Grafström & Ola Spjuth
A virtual machine demonstrating the RDFIO extension [1] for for enabling import, export and SPARQL querying in Semantic MediaWiki [2] wikis, as recently published in [3]. The script to generate this virtual machine is available in [4].
Instructions
1. Download the .ova file2. Import the .ova file in a virtual machine player like VirtualBox of VMWare3. Start the virtual machine4. Log in as Ubuntu (no password required, but it is "changethis..." if you need it)5. Highly recommended...

Example wiki content for RDFIO demonstrator II: DrugMet data imported into Semantic MediaWiki

Samuel Lampa, Egon Willighagen, Pekka Kohonen, ALISON KING, Denny Vrandečić, Roland Grafström & Ola Spjuth
This file is a MediaWiki XML dump of the wiki content generated for Demonstrator II in the RDFIO article [1], importing the open part of the DrugMet dataset, extracted from WikiData [2].
They are exported using a command like:

cd WIKIDIR
php maintenance/dumpBackup.php --current | gzip -c > FILENAME.xml.gz

They can be imported into a Semantic MediaWiki enabled MediaWiki wiki, using the command:

cd WIKIDIR
php maintenance/importDump.php FILENAME.xml.gz

License information

See the WikiData front page page for information about the license of data...

Example wiki content for RDFIO demonstrator II: DrugMet data imported into Semantic MediaWiki

Samuel Lampa, Egon Willighagen, Pekka Kohonen, ALISON KING, Denny Vrandečić, Roland Grafström & Ola Spjuth
This file is a MediaWiki XML dump of the wiki content generated for Demonstrator II in the RDFIO article [1], importing the open part of the DrugMet dataset, extracted from WikiData [2].
They are exported using a command like:

cd WIKIDIR
php maintenance/dumpBackup.php --current | gzip -c > FILENAME.xml.gz

They can be imported into a Semantic MediaWiki enabled MediaWiki wiki, using the command:

cd WIKIDIR
php maintenance/importDump.php FILENAME.xml.gz

License information

See the WikiData front page page for information about the license of data...

Example wiki content for RDFIO demonstrator I: OrphaNet data imported into Semantic MediaWiki

Samuel Lampa, Egon Willighagen, Pekka Kohonen, ALISON KING, Denny Vrandečić, Roland Grafström & Ola Spjuth
This file is a MediaWiki XML dump of the wiki content generated for Demonstrator I in the RDFIO article [1], importing the open part of the OrphaNet dataset [2], converted to RDF in the Bio2RDF project [3].
They are exported using a command like:

cd WIKIDIR
php maintenance/dumpBackup.php --current | gzip -c > FILENAME.xml.gz

They can be imported into a Semantic MediaWiki enabled MediaWiki wiki, using the command:

cd WIKIDIR
php maintenance/importDump.php FILENAME.xml.gz

License information

See this page for information and links to...

Example wiki content for RDFIO demonstrator I: OrphaNet data imported into Semantic MediaWiki

Samuel Lampa, Egon Willighagen, Pekka Kohonen, ALISON KING, Denny Vrandečić, Roland Grafström & Ola Spjuth
This file is a MediaWiki XML dump of the wiki content generated for Demonstrator I in the RDFIO article [1], importing the open part of the OrphaNet dataset [2], converted to RDF in the Bio2RDF project [3].
They are exported using a command like:

cd WIKIDIR
php maintenance/dumpBackup.php --current | gzip -c > FILENAME.xml.gz

They can be imported into a Semantic MediaWiki enabled MediaWiki wiki, using the command:

cd WIKIDIR
php maintenance/importDump.php FILENAME.xml.gz

License information

See this page for information and links to...

Machine Learning in Drug Discovery

Jonathan Alvarsson, Samuel Lampa, Claes Andersson, Lars Carlsson, Jarl E.S. Wikberg & Ola Spjuth
Machine Learning in Drug Discovery, Swedish e-Science Academy 2015, Arlandastad, Stockholm

Machine Learning in Drug Discovery

Jonathan Alvarsson, Samuel Lampa, Claes Andersson, Lars Carlsson, Jarl E.S. Wikberg & Ola Spjuth
Machine Learning in Drug Discovery, Swedish e-Science Academy 2015, Arlandastad, Stockholm

e-Science for Cancer Prevention and Control (eCPC) - a flagship project for the Swedish e-Science Research Centre

Ola Spjuth
The SeRC flagship project e-Science for Cancer Prevention and Control (eCPC) aims to use e-Science methods and technologies to answer the research question: How can we model individual variation in cancer risk to develop better cancer prevention and control strategies? Individual variation may be measured by different biomarkers or environmental exposures, and prevention and control strategies include screening and vaccination.eCPC will use data integration, system biology, machine learning and simulation to address the above research...

e-Science for Cancer Prevention and Control (eCPC) - a flagship project for the Swedish e-Science Research Centre

Ola Spjuth
The SeRC flagship project e-Science for Cancer Prevention and Control (eCPC) aims to use e-Science methods and technologies to answer the research question: How can we model individual variation in cancer risk to develop better cancer prevention and control strategies? Individual variation may be measured by different biomarkers or environmental exposures, and prevention and control strategies include screening and vaccination.eCPC will use data integration, system biology, machine learning and simulation to address the above research...

Poster: e-Science enables improved diagnostics of Chronic Myeloid Leukemia (CML) with next-generation sequencing

Ola Spjuth, Wesley Schaaal & Adam Ameur
We have used long-read PacBio sequencing to detect resistance mutations in BCR-ABL1. In contrast to other technologies, the PacBio reads are long enough to coverthe entire gene so that clonal composition can be assessed, with the idea that compound mutations may be significant for Resistance. The assay has a higher sensitivity as compared to Sanger’s sequencing and mutations down to 0.5% canbe detected.

essence-cml-2015.pdf

Ola Spjuth, Wesley Schaaal & Adam Ameur
We have used long-read PacBio sequencing to detect resistance mutations in BCR-ABL1. In contrast to other technologies, the PacBio reads are long enough to coverthe entire gene so that clonal composition can be assessed, with the idea that compound mutations may be significant for Resistance. The assay has a higher sensitivity as compared to Sanger’s sequencing and mutations down to 0.5% canbe detected.

Raw datasets for Large Scale SVM Experiment(s)

Jonathan Alvarsson, Samuel Lampa & Ola Spjuth
Raw data for the study titled "Large-scale ligand-based predictive modelling using support vector machines" and available at https://pharmb.io/publication/2016-large-scale-svm and http://dx.doi.org/10.1186/s13321-016-0151-5

Changelog:
V2: Add textfiles with checksums (md5 and sha1).
V3: Remove old tarball without checksums.

Raw datasets for Large Scale SVM Experiment(s)

Jonathan Alvarsson, Samuel Lampa & Ola Spjuth
Raw data for the study titled "Large-scale ligand-based predictive modelling using support vector machines" and available at https://pharmb.io/publication/2016-large-scale-svm and http://dx.doi.org/10.1186/s13321-016-0151-5

Changelog:
V2: Add textfiles with checksums (md5 and sha1).

Virtual Machine with Case Study workflow in Jupyter Notebook

Samuel Lampa, Jonathan Alvarsson & Ola Spjuth
A virtual machine with the case study workflow for SciLuigi, runnable from within a Jupyter Notebook. 
Usage:
1. Import the .ova image into a Virtual Machine software such as Virtual box.
2. Start the virtual machine.
3. Log in with ubuntu and changethis...
4. Open a terminal and execute the passwd command, to immediately set a new password.
5. Click the "Open Jupyter Notebook" icon on the desktop.6. Inside Jupyter, click: Cell > Run all cells
7. The workflow...

Virtual Machine with Case Study workflow in Jupyter Notebook

Samuel Lampa, Jonathan Alvarsson & Ola Spjuth
A virtual machine with the case study workflow for SciLuigi, runnable from within a Jupyter Notebook. 
Usage:
1. Import the .ova image into a Virtual Machine software such as Virtual box.
2. Start the virtual machine.
3. Log in with ubuntu and changethis...
4. Open a terminal and execute the passwd command, to immediately set a new password.
5. Click the "Open Jupyter Notebook" icon on the desktop.6. Inside Jupyter, click: Cell > Run all cells
7. The workflow...

Resource Types

  • Dataset
    22
  • Image
    6
  • Software
    4
  • Audiovisual
    2
  • Collection
    1
  • Text
    1

Publication Year

  • 2018
    5
  • 2017
    19
  • 2016
    12

Registration Year

  • 2018
    6
  • 2017
    17
  • 2016
    13

Data Centers

  • figshare Academic Research System
    29
  • ZENODO - Research. Shared.
    5
  • Beijing Genomics Institute
    1
  • University of Cambridge
    1