Genome sequencing and transcriptome analyses of the Siberian hamster hypothalamus identify mechanisms for seasonal energy balance

We thank the manuscript reviewers for constructive feedback; David G. Hazlerigg, Cristina Saenz de Miera, and Valerie Simonneaux for genome sequence contributions; Nicolas Scrutton and Lindsey Duguid for expert technical assistance; and Michael Jarsulic for technical assistance on the high-performance computing clusters. This project was supported by a project research grant from The British Society for Neuroendocrinology (to T.J.S.); Grants BB/M021629/1 and BB/M001555/1 (to F.J.P.E.) from the Biotechnology and Biological Sciences Research Council, and Grants UL1-TR000430 (to T.J.S. and B.J.P.) and R01-AI067406 (to B.J.P.) from the National Institutes of Health. T.J.S. is funded by The Leverhulme Trust. The Center for Research Informatics was supported by the Biological Sciences Division at the University of Chicago with additional support provided by the Institute for Translational Medicine/Clinical and Translational award (NIH 5UL1TR002389-02) and the University of Chicago Comprehensive Cancer Center Support Grant (NIH Grant P30CA014599). The bioinformatics analysis was performed on high-performance computing clusters at the Center for Research Informatics, Biological Sciences Division. P.B. was funded by the Scottish Government Rural and Environment Science and Analytical Services Division grant to the Rowett Institute.Peer reviewedPublisher PD

Biofeedback - March 2013

Archived record for the USA Biomedical Library newsletter for March 2013. Content includes: Director\u27s Notes Print From Anywhere Arrives at the Biomedical Library AccessSurgery Upgraded to Unlimited Access NIH Public Access Policy Custom Curriculum from AccessMedicine and AccessSurgery PubReader View: A new Way to Read Articles in PMC Informatics CE Course at Biomedical Library PB&J Day for Bay Area Food Bank CamStudio Screencasting Program Pew Internet & American Life Project Statistics Tech Corner: Google Reader Replacements MEDLINE Statistics Faculty Publication

Developing a 'personalome' for precision medicine: emerging methods that compute interpretable effect sizes from single-subject transcriptomes

The development of computational methods capable of analyzing -omics data at the individual level is critical for the success of precision medicine. Although unprecedented opportunities now exist to gather data on an individual's -omics profile (personalome'), interpreting and extracting meaningful information from single-subject -omics remain underdeveloped, particularly for quantitative non-sequence measurements, including complete transcriptome or proteome expression and metabolite abundance. Conventional bioinformatics approaches have largely been designed for making population-level inferences about average' disease processes; thus, they may not adequately capture and describe individual variability. Novel approaches intended to exploit a variety of -omics data are required for identifying individualized signals for meaningful interpretation. In this review-intended for biomedical researchers, computational biologists and bioinformaticians-we survey emerging computational and translational informatics methods capable of constructing a single subject's personalome' for predicting clinical outcomes or therapeutic responses, with an emphasis on methods that provide interpretable readouts. Key points: (i) the single-subject analytics of the transcriptome shows the greatest development to date and, (ii) the methods were all validated in simulations, cross-validations or independent retrospective data sets. This survey uncovers a growing field that offers numerous opportunities for the development of novel validation methods and opens the door for future studies focusing on the interpretation of comprehensive personalomes' through the integration of multiple -omics, providing valuable insights into individual patient outcomes and treatments.National Institute of Health (NIH)/Office of the Director Precision Medicine Initiative [1UG3OD023171-01]; Precision Medicine Initiative of the Center for Biomedical Informatics and Biostatistics of the University of Arizona Health Sciences; NIH/National Heart, Lung, and Blood Institute [HL126609-01, HL132523, U01 HL125208]; NIH/National Cancer Institute [P30CA023074, 1R01CA190696-01]; NIH/National Institute of Allergy and Infectious Diseases [U01AI122275-01]Open access articleThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

The development of non-coding RNA ontology

Identification of non-coding RNAs (ncRNAs) has been significantly improved over the past decade. On the other hand, semantic annotation of ncRNA data is facing critical challenges due to the lack of a comprehensive ontology to serve as common data elements and data exchange standards in the field. We developed the Non-Coding RNA Ontology (NCRO) to handle this situation. By providing a formally defined ncRNA controlled vocabulary, the NCRO aims to fill a specific and highly needed niche in semantic annotation of large amounts of ncRNA biological and clinical data

The Global academic research organization network: Data sharing to cure diseases and enable learning health systems.

Introduction:Global data sharing is essential. This is the premise of the Academic Research Organization (ARO) Council, which was initiated in Japan in 2013 and has since been expanding throughout Asia and into Europe and the United States. The volume of data is growing exponentially, providing not only challenges but also the clear opportunity to understand and treat diseases in ways not previously considered. Harnessing the knowledge within the data in a successful way can provide researchers and clinicians with new ideas for therapies while avoiding repeats of failed experiments. This knowledge transfer from research into clinical care is at the heart of a learning health system. Methods:The ARO Council wishes to form a worldwide complementary system for the benefit of all patients and investigators, catalyzing more efficient and innovative medical research processes. Thus, they have organized Global ARO Network Workshops to bring interested parties together, focusing on the aspects necessary to make such a global effort successful. One such workshop was held in Austin, Texas, in November 2017. Representatives from Japan, Taiwan, Singapore, Europe, and the United States reported on their efforts to encourage data sharing and to use research to inform care through learning health systems. Results:This experience report summarizes presentations and discussions at the Global ARO Network Workshop held in November 2017 in Austin, TX, with representatives from Japan, Korea, Singapore, Taiwan, Europe, and the United States. Themes and recommendations to progress their efforts are explored. Standardization and harmonization are at the heart of these discussions to enable data sharing. In addition, the transformation of clinical research processes through disruptive innovation, while ensuring integrity and ethics, will be key to achieving the ARO Council goal to overcome diseases such that people not only live longer but also are healthier and happier as they age. Conclusions:The achievement of global learning health systems will require further exploration, consensus-building, funding aligned with incentives for data sharing, standardization, harmonization, and actions that support global interests for the benefit of patients

Cancer Informatics for Cancer Centers (CI4CC): Building a Community Focused on Sharing Ideas and Best Practices to Improve Cancer Care and Patient Outcomes.

Cancer Informatics for Cancer Centers (CI4CC) is a grassroots, nonprofit 501c3 organization intended to provide a focused national forum for engagement of senior cancer informatics leaders, primarily aimed at academic cancer centers anywhere in the world but with a special emphasis on the 70 National Cancer Institute-funded cancer centers. Although each of the participating cancer centers is structured differently, and leaders' titles vary, we know firsthand there are similarities in both the issues we face and the solutions we achieve. As a consortium, we have initiated a dedicated listserv, an open-initiatives program, and targeted biannual face-to-face meetings. These meetings are a place to review our priorities and initiatives, providing a forum for discussion of the strategic and pragmatic issues we, as informatics leaders, individually face at our respective institutions and cancer centers. Here we provide a brief history of the CI4CC organization and meeting highlights from the latest CI4CC meeting that took place in Napa, California from October 14-16, 2019. The focus of this meeting was "intersections between informatics, data science, and population science." We conclude with a discussion on "hot topics" on the horizon for cancer informatics

Integrating Emerging Areas of Nursing Science into PhD Programs

The Council for the Advancement of Nursing Science aims to “facilitate and recognize life-long nursing science career development” as an important part of its mission. In light of fast-paced advances in science and technology that are inspiring new questions and methods of investigation in the health sciences, the Council for the Advancement of Nursing Science convened the Idea Festival for Nursing Science Education and appointed the Idea Festival Advisory Committee to stimulate dialogue about linking PhD education with a renewed vision for preparation of the next generation of nursing scientists. Building on the 2010 American Association of Colleges of Nursing Position Statement “The Research-Focused Doctoral Program in Nursing: Pathways to Excellence,” Idea Festival Advisory Committee members focused on emerging areas of science and technology that impact the ability of research-focused doctoral programs to prepare graduates for competitive and sustained programs of nursing research using scientific advances in emerging areas of science and technology. The purpose of this article is to describe the educational and scientific contexts for the Idea Festival, which will serve as the foundation for recommendations for incorporating emerging areas of science and technology into research-focused doctoral programs in nursing

1st INCF Workshop on Global Portal Services for Neuroscience

The goal of this meeting was to map out existing portal services for neuroscience, identify their features and future plans, and outline opportunities for synergistic developments. The workshop discussed alternative formats of future global and integrated portal services

Cryo-EM structure of translesion DNA synthesis polymerase ζ with a base pair mismatch

[EN] The B-family multi-subunit DNA polymerase ζ (Polζ) is important for translesion DNA synthesis (TLS) during replication, due to its ability to extend synthesis past nucleotides opposite DNA lesions and mismatched base pairs. We present a cryo-EM structure of Saccharomyces cerevisiae Polζ with an A:C mismatch at the primer terminus. The structure shows how the Polζ active site responds to the mismatched duplex DNA distortion, including the loosening of key protein-DNA interactions and a fingers domain in an “open” conformation, while the incoming dCTP is still able to bind for the extension reaction. The structure of the mismatched DNA-Polζ ternary complex reveals insights into mechanisms that either stall or favor continued DNA synthesis in eukaryotes.This work was funded by grants R01-GM124047 (A.K.A and L.P) and R35-GM13170 (A.K.A) from the National Institutes of Health (NIH). I.U.-B was supported by a grant PID2019-104423GB-I00/AEI/10.13039/501100011033 from the Spanish State Research Agency and by the Basque Excellence Research Centre program. Most of the cryo-EM work was performed at the Simons Electron Microscopy Center and National Resource for Automated Molecular Microscopy, located at the New York Structural Biology Center, supported by grants from the Simons Foundation (SF349247), NYSTAR, and the NIH National Institute of General Medical Sciences (GM103310), with additional support from Agouron Institute (F00316), NIH (OD019994) and NIH (RR029300). Computing resources needed for this work were provided in part by the High Performance Computing facility of the Icahn School of Medicine at Mount Sinai. Molecular graphics and analyses were performed with UCSF Chimera, developed by the Resource for Biocomputing, Visualization, and Informatics at the University of California, San Francisco, with support from NIH P41-GM103311

Negative findings in electronic health records and biomedical ontologies: a realist approach

PURPOSE—A substantial fraction of the observations made by clinicians and entered into patient records are expressed by means of negation or by using terms which contain negative qualifiers (as in “absence of pulse” or “surgical procedure not performed”). This seems at first sight to present problems for ontologies, terminologies and data repositories that adhere to a realist view and thus reject any reference to putative non-existing entities. Basic Formal Ontology (BFO) and Referent Tracking (RT) are examples of such paradigms. The purpose of the research here described was to test a proposal to capture negative findings in electronic health record systems based on BFO and RT. METHODS—We analysed a series of negative findings encountered in 748 sentences taken from 41 patient charts. We classified the phenomena described in terms of the various top-level categories and relations defined in BFO, taking into account the role of negation in the corresponding descriptions. We also studied terms from SNOMED-CT containing one or other form of negation. We then explored ways to represent the described phenomena by means of the types of representational units available to realist ontologies such as BFO. RESULTS—We introduced a new family of ‘lacks’ relations into the OBO Relation Ontology. The relation lacks_part, for example, defined in terms of the positive relation part_of, holds between a particular p and a universal U when p has no instance of U as part. Since p and U both exist, assertions involving ‘lacks_part’ and its cognates meet the requirements of positivity. CONCLUSION—By expanding the OBO Relation Ontology, we were able to accommodate nearly all occurrences of negative findings in the sample studied