Target Gene Notebook: Connecting genetics and drug discovery

AbstractTarget Gene Notebook was developed to enable more efficient linking of genetic associations to functional biological information. This process is essential to translating genetic insights into therapeutic hypotheses and, eventually, drug discovery. Although many public databases provide access to unfiltered genome annotations and genetic results, there was no existing tool to maintain group curation and integration with proprietary experimental data. We provide Target Gene Notebook freely via the MIT open-source license for the purposes of assisting therapeutic target evaluation and the creation of durable institutional and public knowledge bases. Implemented as a Java backend serving mainly Javascript content derived from gene-specific SQLite databases, Target Gene Notebook enables automated access to the most widely used sources of genetic association, expression and protein QTL data, provides intuitive interfaces to credible set and colocalization information, and enables comprehensive literature review and annotation by multiple users simultaneously to create a consistent target knowledgebase within an organization or across a consortium. TargetGeneNotebook is freely available from GitHub https://github.com/targetgenenotebook/tgn.git under the MIT open-source end-user license agreement and a live version of the interface is provided at http://tgn.broadinstitute.org/.

Download Full-text

EXPLANe: An Extensible Framework for Poster Annotation with Mobile Devices

10.1101/121178 ◽

2017 ◽

Author(s):

Nikhil Gopal ◽

Andrew Su ◽

Chunlei Wu ◽

Sean D. Mooney

Keyword(s):

Web Services ◽

Open Source ◽

Mobile Devices ◽

Genetic Variants ◽

Poster Session ◽

Biological Information ◽

Text Recognition ◽

Variant Annotation ◽

Link Type

AbstractSummaryScientific posters tend to be brief, unstructured, and generally unsuitable for communication beyond a poster session. This paper describes EXPLANe, a framework for annotating posters using optical text recognition and web services on mobile devices. EXPLANe is demonstrated through an interface to the MyVariant.info variant annotation web services, and provides users a list of biological information linked with genetic variants (as found via extracted RSIDs from annotated posters). This paper delineates the architecture of the application, and includes results of a five-part evaluation we conducted. Researchers and developers can use the existing codebase as a foundation from which to generate their own annotation tabs when analyzing and annotating posters.AvailabilityAlpha EXPLANe software is available as an open source application at https://github.com/ngopal/EXPLANeContactSean D. Mooney ([email protected])

Download Full-text

Faculty Opinions recommendation of Open Source Drug Discovery with the Malaria Box Compound Collection for Neglected Diseases and Beyond.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.726580430.793521561 ◽

2016 ◽

Author(s):

Christine Clayton

Keyword(s):

Drug Discovery ◽

Open Source ◽

Neglected Diseases ◽

Compound Collection ◽

Malaria Box

Download Full-text

Open source tools for geographic analysis in transport planning

Journal of Geographical Systems ◽

10.1007/s10109-020-00342-2 ◽

2021 ◽

Author(s):

Robin Lovelace

Keyword(s):

User Interface ◽

Open Source ◽

Citizen Participation ◽

Simulation Software ◽

First Century ◽

Transport Planning ◽

Geographic Analysis ◽

Link Type ◽

Twenty First Century ◽

Interactive Map

AbstractGeographic analysis has long supported transport plans that are appropriate to local contexts. Many incumbent ‘tools of the trade’ are proprietary and were developed to support growth in motor traffic, limiting their utility for transport planners who have been tasked with twenty-first century objectives such as enabling citizen participation, reducing pollution, and increasing levels of physical activity by getting more people walking and cycling. Geographic techniques—such as route analysis, network editing, localised impact assessment and interactive map visualisation—have great potential to support modern transport planning priorities. The aim of this paper is to explore emerging open source tools for geographic analysis in transport planning, with reference to the literature and a review of open source tools that are already being used. A key finding is that a growing number of options exist, challenging the current landscape of proprietary tools. These can be classified as command-line interface, graphical user interface or web-based user interface tools and by the framework in which they were implemented, with numerous tools released as R, Python and JavaScript packages, and QGIS plugins. The review found a diverse and rapidly evolving ‘ecosystem’ tools, with 25 tools that were designed for geographic analysis to support transport planning outlined in terms of their popularity and functionality based on online documentation. They ranged in size from single-purpose tools such as the QGIS plugin AwaP to sophisticated stand-alone multi-modal traffic simulation software such as MATSim, SUMO and Veins. Building on their ability to re-use the most effective components from other open source projects, developers of open source transport planning tools can avoid ‘reinventing the wheel’ and focus on innovation, the ‘gamified’ A/B Street https://github.com/dabreegster/abstreet/#abstreet simulation software, based on OpenStreetMap, a case in point. The paper, the source code of which can be found at https://github.com/robinlovelace/open-gat, concludes that, although many of the tools reviewed are still evolving and further research is needed to understand their relative strengths and barriers to uptake, open source tools for geographic analysis in transport planning already hold great potential to help generate the strategic visions of change and evidence that is needed by transport planners in the twenty-first century.

Download Full-text

chewBBACA: A complete suite for gene-by-gene schema creation and strain identification

10.1101/173146 ◽

2017 ◽

Cited By ~ 5

Author(s):

Mickael Silva ◽

Miguel Machado ◽

Diogo N. Silva ◽

Mirko Rossi ◽

Jacob Moran-Gilad ◽

...

Keyword(s):

Open Source ◽

Core Genome ◽

Bacterial Species ◽

Outbreak Detection ◽

Strain Identification ◽

List Type ◽

Whole Genome ◽

Link Type ◽

The Creation ◽

Allele Calling

ABSTRACTGene-by-gene approaches are becoming increasingly popular in bacterial genomic epidemiology and outbreak detection. However, there is a lack of open-source scalable software for schema definition and allele calling for these methodologies. The chewBBACA suite was designed to assist users in the creation and evaluation of novel whole-genome or core-genome gene-by-gene typing schemas and subsequent allele calling in bacterial strains of interest. The software can run in a laptop or in high performance clusters making it useful for both small laboratories and large reference centers. ChewBBACA is available athttps://github.com/B-UMMI/chewBBACAor as a docker image athttps://hub.docker.com/r/ummidock/chewbbaca/.DATA SUMMARYAssembled genomes used for the tutorial were downloaded from NCBI in August 2016 by selecting those submitted asStreptococcus agalactiaetaxon or sub-taxa. All the assemblies have been deposited as a zip file in FigShare (https://figshare.com/s/9cbe1d422805db54cd52), where a file with the original ftp link for each NCBI directory is also available.Code for the chewBBACA suite is available athttps://github.com/B-UMMI/chewBBACAwhile the tutorial example is found athttps://github.com/B-UMMI/chewBBACA_tutorial.I/We confirm all supporting data, code and protocols have been provided within the article or through supplementary data files. ⊠IMPACT STATEMENTThe chewBBACA software offers a computational solution for the creation, evaluation and use of whole genome (wg) and core genome (cg) multilocus sequence typing (MLST) schemas. It allows researchers to develop wg/cgMLST schemes for any bacterial species from a set of genomes of interest. The alleles identified by chewBBACA correspond to potential coding sequences, possibly offering insights into the correspondence between the genetic variability identified and phenotypic variability. The software performs allele calling in a matter of seconds to minutes per strain in a laptop but is easily scalable for the analysis of large datasets of hundreds of thousands of strains using multiprocessing options. The chewBBACA software thus provides an efficient and freely available open source solution for gene-by-gene methods. Moreover, the ability to perform these tasks locally is desirable when the submission of raw data to a central repository or web services is hindered by data protection policies or ethical or legal concerns.

Download Full-text

The Popgen Pipeline Platform: A Software Platform for Facilitating Population Genomic Analyses

10.1101/785774 ◽

2019 ◽

Author(s):

Andrew Webb ◽

Jared Knoblauch ◽

Nitesh Sabankar ◽

Apeksha Sukesh Kallur ◽

Jody Hey ◽

...

Keyword(s):

Open Source ◽

Development Time ◽

End Users ◽

File Format ◽

Software Platform ◽

Format Conversion ◽

Link Type ◽

Population Genomic ◽

Genomic Analyses ◽

File Format Conversion

AbstractHere we present the Pop-Gen Pipeline Platform (PPP), a software platform with the goal of reducing the computational expertise required for conducting population genomic analyses. The PPP was designed as a collection of scripts that facilitate common population genomic workflows in a consistent and standardized Python environment. Functions were developed to encompass entire workflows, including: input preparation, file format conversion, various population genomic analyses, output generation, and visualization. By facilitating entire workflows, the PPP offers several benefits to prospective end users - it reduces the need of redundant in-house software and scripts that would require development time and may be error-prone, or incorrect. The platform has also been developed with reproducibility and extensibility of analyses in mind. The PPP is an open-source package that is available for download and use at https://ppp.readthedocs.io/en/latest/PPP_pages/install.html

Download Full-text

COMPUTATIONAL APPROACHES FOR DRUG DISCOVERY FROM MEDICINAL PLANTS IN THE ERA OF DATA DRIVEN RESEARCH

INDIAN DRUGS ◽

10.53879/id.58.08.12930 ◽

2021 ◽

Vol 58 (08) ◽

pp. 7-23

Author(s):

Pratibha Pansari ◽

Keyword(s):

Drug Discovery ◽

Medicinal Plants ◽

In Silico ◽

Drug Target ◽

Target Gene ◽

Scientific Work ◽

Data Driven ◽

Network Pharmacology ◽

Gene Pathway ◽

Topological Network

The significant scientific work on the development of bio-active compound databases, computational technologies, and the integration of Information Technology with Biotechnology has brought a revolution in the domain of drug discovery. These tools facilitate the medicinal plant-based in silico drug discovery, which has become the frontier of pharmacological science. In this review article, we elucidate the methodology of in silico drug discovery for the medicinal plants and present an outlook on recent tools and technologies. Further, we explore the multi-component, multi-target, and multi-pathway mechanism of the bio-active compounds with the help of Network Pharmacology, which enables us to create a topological network between drug, target, gene, pathway, and disease.

Download Full-text

RETHINKING EPISTEMIC INCENTIVES: HOW PATIENT-CENTERED, OPEN SOURCE DRUG DISCOVERY GENERATES MORE VALUABLE KNOWLEDGE SOONER

Episteme ◽

10.1017/epi.2013.33 ◽

2013 ◽

Vol 10 (4) ◽

pp. 417-439

Author(s):

Alexandra Bradner

Keyword(s):

Drug Discovery ◽

Open Source ◽

Molecular Probes ◽

Monetary Incentives ◽

Patient Centered ◽

For Profit ◽

Research Investment ◽

Collective Beliefs ◽

Physician Scientists ◽

Initial Research

AbstractDrug discovery traditionally has occurred behind closed doors in for-profit corporations hoping to develop best-selling medicines that recoup initial research investment, sustain marketing infrastructures, and pass on healthy returns to shareholders. Only corporate Pharma has the man- and purchasing-power to synthesize the thousands of molecules needed to find a new drug and to conduct the clinical trials that will make the drug legal. Against this view, individual physician-scientists have suggested that the promise of applied genomics work calls for a new form of social organization – the open source sharing of molecular probes – in order to speed the generation and understanding of new therapeutics. Recent successes in open source drug discovery show it is possible to produce valuable, empirically adequate, and sustainable collective beliefs without secrecy, proprietary attitudes, initial cooperation from Pharma, or outsized monetary incentives. After reviewing and differentiating these successes, I diagnose the source of this healthy new epistemic strategy.

Download Full-text

Dashing: fast and accurate genomic distances with HyperLogLog

Genome Biology ◽

10.1186/s13059-019-1875-0 ◽

2019 ◽

Vol 20 (1) ◽

Cited By ~ 9

Author(s):

Daniel N. Baker ◽

Ben Langmead

Keyword(s):

Open Source ◽

Software Tool ◽

Estimation Methods ◽

Cardinality Estimation ◽

Link Type ◽

Wide Range

AbstractDashing is a fast and accurate software tool for estimating similarities of genomes or sequencing datasets. It uses the HyperLogLog sketch together with cardinality estimation methods that are specialized for set unions and intersections. Dashing summarizes genomes more rapidly than previous MinHash-based methods while providing greater accuracy across a wide range of input sizes and sketch sizes. It can sketch and calculate pairwise distances for over 87K genomes in 6 minutes. Dashing is open source and available at https://github.com/dnbaker/dashing.

Download Full-text