Biocuration introduction

1. What is biocuration?

2. Biocurationinvolves organizing and structuring biological data to make it more accessible and
interpretable for researchers. Researchdata is one of the most valuable things we have, but big data
and data explosionhave made more data available thanever. Biocurationdistills data into knowledge
and makes it computable, unlocking the full potential of biological data.

3. The Value of Biocuration in the Data
Explosion Era
Researchdata is one of the most
valuable things we have, and
withmore data available than
ever, biocurationis necessary to
distill this data into knowledge.
Biocurationexacts knowledge
fromunstructured biological
data into a structured,
computable form, helping us
handle the vast amounts of data
available.
Biocurationensures that data is
easily accessible and
comprehensive, providing a
reliable basis for computational
analysis and further research.

4. Biocuration Goals and Achievements
1
Accurate and Comprehensive
Representation
Biocurationaims to provide anaccurate and
comprehensive representationof biological
knowledge, making it accessible to working
scientists.
2
Efficient Data Management
Biocurationenables efficient management of
large biological datasets, fromscientific
literature and databases to experiments and
researchpapers.
3
Evidence-Based Research
Biocurationprovides a basis for evidence-
based researchand enables researchers to
access reliable, well-annotated data to
support their work.

5. The Role of Biocuration
Data Cleaning
Biocurationremoves
inconsistencies, errors, and
redundancies from
datasets, leading to cleaner
and more reliable data.
Standardization
Biocurationestablishes
standardized formats,
ontologies, and
terminologies, enabling
effective integrationand
interoperability.
Data Enrichment
Biocurationadds relevant
metadata, annotations, and
contextual information,
enhancing the value and
utility of the data.

6. The Convergent Endeavors of
Biocuration
The goals of biocurationare
achieved throughthe combined
efforts of biocurators, software
developers, and researchers in
bioinformatics.
Effective collaborationis crucial
to biocuration, enabling
thoroughand accurate analysis
of biological data fromvarious
sources.
Highly skilled biocurators are
essential to the success of
biocuration, ensuring that
biological informationis
accurately processed and
annotated.

7. Biocuration: Ensuring Data Quality
and Relevance
1
Data Quality Control
Biocurationensures that data is up-to-date
and dynamic, meeting the evolving needs of
the scientific community and researchusers.
2
Interdisciplinary Approach
Biocurationinvolves aninterdisciplinary
approach, bringing together experts in
biology, data science, and technology for a
comprehensive analysis of biological data.
3
Contextual Information
Biocurationprovides relevant contextual
informationand metadata, enhancing the
value and relevance of data for researchers
and clinicians.

8. Biocuration: An Integral Part of
Biological Research
1 Efficient
Experimentation
Biocurationenables
efficient
experimentationand
hypothesis testing,
providing a foundationof
accurate and
comprehensive data.
2 Informed Decision-
Making
Access to reliable,
annotated data through
biocurationenables
informed decision-
making inresearchand
clinical practice.
3 Continuing
Advancements
Continuing
advancements in
biocurationare
necessary to keep pace
withthe expanding
availability and
complexity of biological
data.

9. Biocuration: Unlocking the Potential
of Biological Data
BiocurationDefinition Organizing, annotating, and structuring
biological data fromvarious sources to create
comprehensive and reliable informationfor
researchers and clinicians.
BiocurationProcess Collection, processing, and standardizationof
data fromvarious scientific sources, including
researchpapers, experiments, and databases,
to create easily accessible and valuable
information.
Benefits of Biocuration Provides reliable and accurate data for
researchand clinical practice, enables
efficient data management, and supports
evidence-based decision-making.

10. Disease Ontology Team
The Disease Ontology is a project ofthe University ofMaryland School ofMedicine, Institute of
Genome Sciences
LynnSchriml - PI - Institute for Genome Sciences
J. AllenBaron- Institute for Genome Sciences
Claudia Sánchez-Beato Johnson- Institute for Genome Sciences
DustinOlley - Institute for Genome Sciences
Mike Schor - Institute for Genome Sciences
SusanBello - The JacksonLaboratory Katharine Bisordi - University of Maryland School of Medicine
Cynthia Bearer - Case WesternReserve University School of Medicine
Victor Felix - Institute for Genome Sciences Carol Greene - University of Maryland School of Medicine
Richard Lichenstein- University of Maryland School of Medicine
Lance Nickel - Institute for Genome Sciences

11. NHGRI GRANT U24HG012557