Biology subjects

Mullen, J.

Publications and source records attributed to Mullen, J..

5 recordsLinked to original sources

bioRxiv2022

Outbreak.info: A standardized, searchable platform to discover and explore COVID-19 resources and data

To combat the ongoing COVID-19 pandemic, scientists have been conducting research at breakneck speeds, producing over 52,000 peer-reviewed articles within the first year. To address the challenge in tracking the vast amount of new research located in separate repositories, we developed outbreak.info Research Library, a standardized, searchable interface of COVID-19 and SARS-CoV-2 resources. Unifying metadata from sixteen repositories, we assembled a collection of over 350,000 publications, clinical trials, datasets, protocols, and other resources as of October 2022. We used a rigorous schema to enforce consistency across different sources and resource types and linked related resources. Researchers can quickly search the latest research across data repositories, regardless of resource type or repository location, via a search interface, public API, and R package. Finally, we discuss the challenges inherent in combining metadata from scattered and heterogeneous resources and provide recommendations to streamline this process to aid scientific research.

bioinformatics↗

bioRxiv2021

BioThings SDK: a toolkit for building high-performance data APIs in biomedical research

SummaryTo meet the increased need of making biomedical resources more accessible and reusable, Web APIs or web services have become a common way to disseminate knowledge sources. The BioThings APIs are a collection of high-performance, scalable, annotation as a service APIs that automate the integration of biological annotations from disparate data sources. This collection of APIs currently includes MyGene.info, MyVariant.info, and MyChem.info for integrating annotations on genes, variants, and chemical compounds, respectively. These APIs are used by both individual researchers and application developers to simplify the process of annotation retrieval and identifier mapping. Here, we describe the BioThings Software Development Kit (SDK), a generalizable and reusable toolkit for integrating data from multiple disparate data sources and creating high-performance APIs. This toolkit allows users to easily create their own BioThings APIs for any data type of interest to them, as well as keep APIs up-to-date with their underlying data sources. Availability and implementationThe BioThings SDK is built in Python and released via PyPI (https://pypi.org/project/biothings/). Its source code is hosted at its github repository (https://github.com/biothings/biothings.api).

bioinformatics↗

bioRxiv2020

Optimising biomedical relationship extraction with BioBERT: Best practices for data creation

Text mining is widely used within the life sciences as an evidence stream for inferring relationships between biological entities. In most cases, conventional string matching is used to identify cooccurrences of given entities within sentences. This limits the utility of text mining results, as they tend to contain significant noise due to weak inclusion criteria. We show that, in the indicative case of protein-protein interactions (PPIs), the majority of sentences containing cooccurrences ({bsim}75%) do not describe any causal relationship. We further demonstrate the feasibility of fine tuning a strong domain-specific language model, BioBERT, to analyse sentences containing cooccurrences and accurately (F1 score: 88.95%) identify functional links between proteins. These strong results come in spite of the deep complexity of the language involved, which limits the accuracy even of expert curators. We establish guidelines for best practices in data creation to this end, including an examination of inter-annotator agreement, of semisupervision, and of rules based alternatives to manual curation, and explore the potential for downstream use of the model to accelerate curation of interactions in the SIGNOR database of causal protein interactions and the IntAct database of experimental evidence for physical protein interactions.

bioinformatics↗

bioRxiv2019

Antagonistic and auxin-dependent phosphoregulation of columella PIN proteins controls lateral root gravitropic setpoint angle in Arabidopsis

Lateral roots of many species are maintained at non-vertical angles with respect to gravity. These gravitropic setpoint angles (GSAs) are intriguing because their maintenance requires that roots are able to effect gravitropic response both with and against the gravity vector. Here we have used the Arabidopsis lateral root in order to investigate the molecular basis of the maintenance of non-vertical GSAs. We show that gravitropism in the lateral root is angle-dependent and that both upward and downward graviresponse requires auxin transport and the generation of auxin asymmetries consistent with the Cholodny-Went model. We show that the symmetry in auxin distribution in lateral roots growing at GSA can be traced back to a net, balanced polarization of PIN3 and PIN7 auxin transporters in the columella cells. Further, upward and downward graviresponse in lateral roots correlates with corresponding changes in PIN3 and PIN7 polar localisation. Finally, we show that auxin, in addition to driving tropic growth in the lateral root, acts within the columella to regulate GSA via the PIN phosphatase subunit RCN1 in a PIN3-dependent and PIN7-independent manner. Together, these findings provide a molecular framework for understanding gravity-dependent nonvertical growth in Arabidopsis lateral roots.

plant biology↗

bioRxiv2018

Drought adaptation in nature by extensive genetic loss-of-function

Visions of a second green revolution empowered by emerging technologies have called for interdisciplinary syntheses to scale up the discovery of functionally definitive gene variants responsible for climate adaptation in plants. We integrated novel approaches using whole genome sequences and satellite remote sensing to identify natural knockout alleles associated with drought histories in wild Arabidopsis thaliana. Genes identified exhibit signatures of parallel molecular evolution, selection for loss-of-function alleles, and shared associations with flowering time phenotypes in directions consistent with longstanding adaptive hypotheses 7 times more often than expected by chance. Artificial knockout lines then confirmed predicted phenotypes experimentally. These findings further challenge popular assumptions about the adaptive value of genetic loss-of-function in nature and inspire new opportunities for engineering climate resilience in crops.\n\nOne sentence summaryWhole genome sequences and satellite-detected droughts point to gene knockouts as valuable genetic fuel for climate adaptation.

evolutionary biology↗