Frontiers in Genomic Assay Technologies: The Grand Challenges in Enabling Data-Intensive Biological Research

Abstract Background Organizing and annotating biological sample data is critical in data-intensive bioinformatics. Unfortunately, metadata formats from a data provider are often incompatible with requirements of a processing tool. There is no broadly accepted standard to organize metadata across biological projects and bioinformatics tools, restricting the portability and reusability of both annotated datasets and analysis software. Results To address this, we present the Portable Encapsulated Project (PEP) specification, a formal specification for biological sample metadata structure. The PEP specification accommodates typical features of data-intensive bioinformatics projects with many biological samples. In addition to standardization, the PEP specification provides descriptors and modifiers for project-level and sample-level metadata, which improve portability across both computing environments and data processing tools. PEPs include a schema validator framework, allowing formal definition of required metadata attributes for data analysis broadly. We have implemented packages for reading PEPs in both Python and R to provide a language-agnostic interface for organizing project metadata. Conclusions The PEP specification is an important step toward unifying data annotation and processing tools in data-intensive biological research projects. Links to tools and documentation are available at http://pep.databio.org/.

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537 Animal Growth and Development—A Scorecard and Recalibration

Journal of Animal Science ◽

10.1093/jas/skab235.131 ◽

2021 ◽

Vol 99 (Supplement_3) ◽

pp. 72-73

Author(s):

Dave E Gerrard ◽

Robert P Rhoads ◽

Honglin Jiang ◽

Samer El-Kadi ◽

Elizabeth R Gilbert ◽

...

Keyword(s):

Public Policy ◽

Cell Biology ◽

Growth And Development ◽

Research Priorities ◽

The Body ◽

Whole Body ◽

Biological Research ◽

Cellular Mechanisms ◽

Grand Challenges ◽

Animal Sciences

Abstract The ASAS Public Policy Committee (PPC) provides updates of Grand Challenges (GCs; www.asas.org/about/public-policy/asas-grand-challenges) to clearly articulate research priorities, to provide science-based information for shaping public policy, and to enhance future funding for research and education programs in animal sciences (AS). In this nexus symposium for 2021, PPC examines previous stated priorities and provides a progress report card and offers additional perspectives and recommendations for research needed to address some of the GCs continuing to face animal agriculture. Among the GC topics is growth and development, a rather broad field of inquiry focused on improving the overall growth efficiency of meat producing animals. The genesis of this discipline and its popularity grew mainly in response to heightened efforts by pharmaceutical companies to identify, develop and adopt novel new growth promotants. This included a myriad of work on the highly heralded technologies involving estrogenic and androgenic implants, somatotropin, and beta-adrenergic agonists. Because the potential application of these technologies was so broad, many disciplines within the animal sciences became involved in the process of creating knowledge around these drivers of productivity. In the process, our understanding of how tissues grow in response to these compounds, under a myriad of other conditions, and our fundamental understanding of the molecular and cellular mechanisms regulating growth and development, expanded significantly. Areas of significant expansion included but were not restricted to: satellite cell biology and myogenesis, whole body and tissue-specific protein synthesis and degradation, growth factor biology, adipogenesis, and repartitioning of nutrients throughout the body. In our quest to increase productivity and product quality, coupled with advances in scientific techniques, long-existing and emerging genetic mutations with desirable traits were studied and mechanisms undergirding their biology began to develop. Applying the most innovative tools for the detailed manipulation of cellular processes, great strides were made during this time. However, this eclectic area of investigation is perhaps more important than ever given the inevitable replacement of growth promotant technologies with new and emerging genomic technologies. Many biological research challenges lie ahead such as applications of gene editing, RNA control, and epigenetic regulation through fetal programming. This presentation will review some of the significant advances made in the growth and development area and explore where significant gains may be possible in the future.

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Linking big biomedical datasets to modular analysis with Portable Encapsulated Projects

10.1101/2020.10.08.331322 ◽

2020 ◽

Author(s):

Nathan C. Sheffield ◽

Michał Stolarczyk ◽

Vincent P. Reuter ◽

André F. Rendeiro

Keyword(s):

Biological Sample ◽

Single Cells ◽

Biological Research ◽

Biomedical Data ◽

Data Annotation ◽

Data Intensive ◽

Sample Data ◽

Modular Analysis ◽

Data Source ◽

Definition Of

Organizing and annotating biological sample data is critical in data-intensive bioinformatics. Unfortunately, incompatibility is common between metadata format of a data source and that required by a processing tool. There is no broadly accepted standard to organize metadata across biological projects and bioinformatics tools, restricting the portability and reusability of both annotated datasets and analysis software. To address this, we present Portable Encapsulated Projects (PEP), a formal specification for biological sample metadata structure. The PEP specification accommodates typical features of data-intensive bioinformatics projects with many samples, whether from individual experiments, organisms, or single cells. In addition to standardization, the PEP specification provides descriptors and modifiers for different organizational layers of a project, which improve portability among computing environments and facilitate use of different processing tools. PEP includes a schema validator framework, allowing formal definition of required metadata attributes for any type of biomedical data analysis. We have implemented packages for reading PEPs in both Python and R to provide a language-agnostic interface for organizing project metadata. PEP therefore presents an important step toward unifying data annotation and processing tools in data-intensive biological research projects.

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Experimental Determination of the Effective Resolution Limit in Thick Specimens at High Voltages

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100116942 ◽

1975 ◽

Vol 33 ◽

pp. 664-665

Author(s):

Mircea Fotino

Keyword(s):

Experimental Approach ◽

Chromatic Aberration ◽

Resolving Power ◽

Biological Research ◽

Specimen Thickness ◽

Resolution Limit ◽

High Voltage Electron Microscopy ◽

Voltage Electron ◽

Resolution Level

The use of thick specimens (0.5 μm to 5.0 μm or more) is one of the most resourceful applications of high-voltage electron microscopy in biological research. However, the energy loss experienced by the electron beam in the specimen results in chromatic aberration and thus in a deterioration of the effective resolving power. This sets a limit to the maximum usable specimen thickness when investigating structures requiring a certain resolution level.An experimental approach is here described in which the deterioration of the resolving power as a function of specimen thickness is determined. In a manner similar to the Rayleigh criterion in which two image points are considered resolved at the resolution limit when their profiles overlap such that the minimum of one coincides with the maximum of the other, the resolution attainable in thick sections can be measured by the distance from minimum to maximum (or, equivalently, from 10% to 90% maximum) of the broadened profile of a well-defined step-like object placed on the specimen.

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Some problems and solutions in electron energy loss spectroscopy of cryosections

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100148666 ◽

1993 ◽

Vol 51 ◽

pp. 566-567

Author(s):

Zhifeng Shao ◽

Ruoya Ho ◽

Andrew P. Somlyo

Keyword(s):

High Resolution ◽

Energy Loss ◽

Electron Energy ◽

Electron Energy Loss Spectroscopy ◽

Biological Research ◽

Specimen Thickness ◽

Elemental Distribution ◽

Electron Dose ◽

Simple Assumption ◽

Electron Energy Loss

Electron energy loss spectroscopy (EELS) has been a powerful tool for high resolution studies of elemental distribution, as well as electronic structure, in thin samples. Its foundation for biological research has been laid out nearly two decades ago, and in the subsequent years it has been subjected to rigorous, but by no means extensive research. In particular, some problems unique to EELS of biological samples, have not been fully resolved. In this article we present a brief summary of recent methodological developments, related to biological applications of EELS, in our laboratory. The main purpose of this work was to maximize the signal to noise ratio (S/N) for trace elemental analysis at a minimum dose, in order to reduce the electron dose and/or time required for the acquisition of high resolution elemental maps of radiation sensitive biological materials.Based on the simple assumption of Poisson distribution of independently scattered electrons, it had been generally assumed that the optimum specimen thickness, at which the S/N is a maximum, must be the total inelastic mean free path of the beam electron in the sample.

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