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Marco Alvarado Cano

dblp:239/8046 · DBLP profile ↗
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3ranked-venue papers
1as first author
3since 2021 · last 2023
0000-0001-6992-8390ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 3 · 1 first-author · 3 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
2 papers
Bioinformatics and computational biology · 100%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › knowledge representation in biology
biomedical knowledge graph
0.712023
BioThings Explorer: a query engine for a federated knowledge graph of biomedical APIs · Bioinform. 2023
Bioinformatics and computational biology › data integration
biomedical data integration
0.612022
BioThings SDK: a toolkit for building high-performance data APIs in biomedical research · Bioinform. 2022
Bioinformatics and computational biology › drug discovery
drug repurposing
0.212023
BioThings Explorer: a query engine for a federated knowledge graph of biomedical APIs · Bioinform. 2023
Bioinformatics and computational biology
identifier mapping
0.212022
BioThings SDK: a toolkit for building high-performance data APIs in biomedical research · Bioinform. 2022

Methods — techniques the papers use, named apart from their topics

semantic annotation · 0.7API chaining · 0.7
YearPublicationVenuePosition
2023 BioThings Explorer: a query engine for a federated knowledge graph of biomedical APIs
abstract
Knowledge graphs are an increasingly common data structure for representing biomedical information. These knowledge graphs can easily represent heterogeneous types of information, and many algorithms and tools exist for querying and analyzing graphs. Biomedical knowledge graphs have been used in a variety of applications, including drug repurposing, identification of drug targets, prediction of drug side effects, and clinical decision support. Typically, knowledge graphs are constructed by centralization and integration of data from multiple disparate sources. Here, we describe BioThings Explorer, an application that can query a virtual, federated knowledge graph derived from the aggregated information in a network of biomedical web services. BioThings Explorer leverages semantically precise annotations of the inputs and outputs for each resource, and automates the chaining of web service calls to execute multi-step graph queries. Because there is no large, centralized knowledge graph to maintain, BioThing Explorer is distributed as a lightweight application that dynamically retrieves information at query time. More information can be found at https://explorer.biothings.io, and code is available at https://github.com/biothings/biothings_explorer.
Jackson Callaghan, Colleen H. Xu, Jiwen Xin, Marco Alvarado Cano, Anders Riutta, Eric Zhou, Rohan Juneja, Yao Yao 0007, Madhumita Narayan, Kristina Hanspers, Ayushi Agrawal, Alexander R. Pico, Chunlei Wu, Andrew I. Su
Bioinform.4
2023 Schema Playground: a tool for authoring, extending, and using metadata schemas to improve FAIRness of biomedical data
abstract
BACKGROUND: Biomedical researchers are strongly encouraged to make their research outputs more Findable, Accessible, Interoperable, and Reusable (FAIR). While many biomedical research outputs are more readily accessible through open data efforts, finding relevant outputs remains a significant challenge. Schema.org is a metadata vocabulary standardization project that enables web content creators to make their content more FAIR. Leveraging Schema.org could benefit biomedical research resource providers, but it can be challenging to apply Schema.org standards to biomedical research outputs. We created an online browser-based tool that empowers researchers and repository developers to utilize Schema.org or other biomedical schema projects. RESULTS: Our browser-based tool includes features which can help address many of the barriers towards Schema.org-compliance such as: The ability to easily browse for relevant Schema.org classes, the ability to extend and customize a class to be more suitable for biomedical research outputs, the ability to create data validation to ensure adherence of a research output to a customized class, and the ability to register a custom class to our schema registry enabling others to search and re-use it. We demonstrate the use of our tool with the creation of the Outbreak.info schema-a large multi-class schema for harmonizing various COVID-19 related resources. CONCLUSIONS: We have created a browser-based tool to empower biomedical research resource providers to leverage Schema.org classes to make their research outputs more FAIR.
Marco Alvarado Cano, Ginger Tsueng, Xinghua Zhou, Jiwen Xin, Laura D. Hughes, Julia Mullen, Andrew I. Su, Chunlei Wu
BMC Bioinform.1
2022 BioThings SDK: a toolkit for building high-performance data APIs in biomedical research
abstract
SUMMARY: To meet the increased need of making biomedical resources more accessible and reusable, Web Application Programming Interfaces (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 IMPLEMENTATION: The 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). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Sebastien Lelong, Xinghua Zhou, Cyrus Afrasiabi, Zhongchao Qian, Marco Alvarado Cano, Ginger Tsueng, Jiwen Xin, Julia Mullen, Yao Yao 0007, Ricardo Avila, Greg Taylor, Andrew I. Su, Chunlei Wu
Bioinform.5