From patients to partners: participant-centric initiatives in biomedical research.

Advances in computing technology and bioinformatics mean that medical research is increasingly characterized by large international consortia of researchers that are reliant on large data sets and biobanks. These trends raise a number of challenges for obtaining consent, protecting participant privacy concerns and maintaining public trust. Participant-centred initiatives (PCIs) use social media technologies to address these immediate concerns, but they also provide the basis for long-term interactive partnerships. Here, we give an overview of this rapidly moving field by providing an analysis of the different PCI approaches, as well as the benefits and challenges of implementing PCIs.

Perspectives and expectations in structural bioinformatics of metalloproteins.

Recent papers highlight the presence of large numbers of compressed angles in metal ion coordination geometries for metalloprotein entries in the worldwide Protein Data Bank, due mainly to multidentate coordination. The prevalence of these compressed angles has raised the controversial idea that significantly populated aberrant or even novel coordination geometries may exist. Some of these papers have undergone severe criticism, apparently due to views held that only canonical coordination geometries exist in significant numbers. While criticism of controversial ideas is warranted and to be expected, we believe that a line was crossed where unfair criticism was put forth to discredit an inconvenient result that compressed angles exist in large numbers, which does not support the dogmatic canonical coordination geometry view. We present a review of the major controversial results and their criticisms, pointing out both good suggestions that have been incorporated in new analyses, but also unfair criticism that was put forth to support a particular view. We also suggest that better science is enabled through: (i) a more collegial and collaborative approach in future critical reviews and (ii) the requirement for a description of methods and data including source code and visualizations that enables full reproducibility of results. Proteins 2017; 85:938-944. © 2016 Wiley Periodicals, Inc.

Personalized respiratory medicine: exploring the horizon, addressing the issues. Summary of a BRN-AJRCCM workshop held in Barcelona on June 12, 2014.

This Pulmonary Perspective summarizes the content and main conclusions of an international workshop on personalized respiratory medicine coorganized by the Barcelona Respiratory Network ( www.brn.cat ) and the AJRCCM in June 2014. It discusses (1) its definition and historical, social, legal, and ethical aspects; (2) the view from different disciplines, including basic science, epidemiology, bioinformatics, and network/systems medicine; (3) the bottlenecks and opportunities identified by some currently ongoing projects; and (4) the implications for the individual, the healthcare system and the pharmaceutical industry. The authors hope that, although it is not a systematic review on the subject, this document can be a useful reference for researchers, clinicians, healthcare managers, policy-makers, and industry parties interested in personalized respiratory medicine.

[Bioinformatics: a key role in oncology]. / Bioinformatique en oncologie: une discipline incontournable.

Bioinformatics is essential in clinical oncology and research. Combining biology, computer science and mathematics, bioinformatics aims to derive useful information from clinical and biological data, often poorly structured, at a large scale. Bioinformatics approaches have reclassified certain cancers based on their molecular and biological presentation, improving treatment selection. Many molecular signatures have been developed and, after validation, some are now usable in clinical practice. Other applications could facilitate daily practice, reduce the risk of error and increase the precision of medical decision-making. Bioinformatics must evolve in accordance with ethical considerations and requires multidisciplinary collaboration. Its application depends on a sound technical foundation that meets strict quality requirements.

Contributions from the 2019 Literature on Bioinformatics and Translational Informatics.

OBJECTIVES: Summarize recent research and select the best papers published in 2019 in the field of Bioinformatics and Translational Informatics (BTI) for the corresponding section of the International Medical Informatics Association Yearbook. METHODS: A literature review was performed for retrieving from PubMed papers indexed with keywords and free terms related to BTI. Independent review allowed the section editors to select a list of 15 candidate best papers which were subsequently peer-reviewed. A final consensus meeting gathering the whole Yearbook editorial committee was organized to finally decide on the selection of the best papers. RESULTS: Among the 931 retrieved papers covering the various subareas of BTI, the review process selected four best papers. The first paper presents a logical modeling of cancer pathways. Using their tools, the authors are able to identify two known behaviours of tumors. The second paper describes a deep-learning approach to predicting resistance to antibiotics in Mycobacterium tuberculosis. The authors of the third paper introduce a Genomic Global Positioning System (GPS) enabling comparison of genomic data with other individuals or genomics databases while preserving privacy. The fourth paper presents a multi-omics and temporal sequence-based approach to provide a better understanding of the sequence of events leading to Alzheimer's Disease. CONCLUSIONS: Thanks to the normalization of open data and open science practices, research in BTI continues to develop and mature. Noteworthy achievements are sophisticated applications of leading edge machine-learning methods dedicated to personalized medicine.

Privacy, the individual and genetic information: a Buddhist perspective.

Bioinformatics is a new field of study whose ethical implications involve a combination of bioethics, computer ethics and information ethics. This paper is an attempt to view some of these implications from the perspective of Buddhism. Privacy is a central concern in both computer/information ethics and bioethics, and with information technology being increasingly utilized to process biological and genetic data, the issue has become even more pronounced. Traditionally, privacy presupposes the individual self but as Buddhism does away with the ultimate conception of an individual self, it has to find a way to analyse and justify privacy that does not presuppose such a self. It does this through a pragmatic conception that does not depend on a positing of the substantial self, which is then found to be unnecessary for an effective protection of privacy. As it may be possible one day to link genetic data to individuals, the Buddhist conception perhaps offers a more flexible approach, as what is considered to be integral to an individual person is not fixed in objectivity but depends on convention.

Contributions from the 2018 Literature on Bioinformatics and Translational Informatics.

OBJECTIVES: To summarize recent research and select the best papers published in 2018 in the field of Bioinformatics and Translational Informatics (BTI) for the corresponding section of the International Medical Informatics Association (IMIA) Yearbook. METHODS: A literature review was performed for retrieving from PubMed papers indexed with keywords and free terms related to BTI. Independent review allowed the two section editors to select a list of 14 candidate best papers which were subsequently peer-reviewed. A final consensus meeting gathering the whole IMIA Yearbook editorial committee was organized to finally decide on the selection of the best papers. RESULTS: Among the 636 retrieved papers published in 2018 in the various subareas of BTI, the review process selected four best papers. The first paper presents a computational method to identify molecular markers for targeted treatment of acute myeloid leukemia using multi-omics data (genome-wide gene expression profiles) and in vitro sensitivity to 160 chemotherapy drugs. The second paper describes a deep neural network approach to predict the survival of patients suffering from glioma on the basis of digitalised pathology images and genomics biomarkers. The authors of the third paper adopt a pan-cancer approach to take benefit of multi-omics data for drug repurposing. The fourth paper presents a graph-based semi-supervised method to accurate phenotype classification applied to ovarian cancer. CONCLUSIONS: Thanks to the normalization of open data and open science practices, research in BTI continues to develop and mature. Noteworthy achievements are sophisticated applications of leading edge machine-learning methods dedicated to personalized medicine.

When Biology Gets Personal: Hidden Challenges of Privacy and Ethics in Biological Big Data.

High-throughput technologies for biological data acquisition are advancing at an increasing pace. Most prominently, the decreasing cost of DNA sequencing has led to an exponential growth of sequence information, including individual human genomes. This session of the 2019 Pacific Symposium on Biocomputing presents the distinctive privacy and ethical challenges related to the generation, storage, processing, study, and sharing of individuals' biological data generated by multitude of technologies including but not limited to genomics, proteomics, metagenomics, bioimaging, biosensors, and personal health trackers. The mission is to bring together computational biologists, experimental biologists, computer scientists, ethicists, and policy and lawmakers to share ideas, discuss the challenges related to biological data and privacy.

Integrative Biology and Big-Data-Centrism: Mapping out a Bioscience Ethics Perspective with a S.W.O.T. Matrix.

In current biomedicine, omics technologies drive systems-oriented modes of research to achieve a more holistic and personalized view of health and disease. This shift in scientific approach co-occurs with an era of biocapitalism characterized by markets for biomaterial (e.g., DNA, cells, and tissues) as exploitable resources, high-throughput technologies as tools, and "Big Data" as currency. Prediagnostics and genomics-based analyses successfully entered the public domain more or less unfiltered, offering numerous business opportunities envisioning individuals to contribute to the health sector by providing biomaterial and data as well as by using technology, thus becoming participants and informed coproducers of health. Exploring strengths and weaknesses, as well as opportunities and threats by S.W.O.T. analysis, we highlight some chances, pitfalls, and biases of this sector from a bioscience ethics stance. We conclude that the shift from diagnostic to predictive interpretation of data that comes along with integrative biology seems to escape the general and sometimes the experts' awareness. Moreover, rapid translation into products for the global health market is based on marketable views on health and disease that in turn affect basic research through, for example, funding policies and the research questions being asked. Along with this, biological reductionism is revived fuelling simplified understandings of the genotype phenotype relationship in terms of biology and the human dimension in a broader sense, as well as visions of achieving human perfection through novel biotechnologies.

Where is the human in the data? A guide to ethical data use.

Being asked to write about the ethics of big data is a bit like being asked to write about the ethics of life. Big data is now integral to so many aspects of our daily lives-communication, social interaction, medicine, access to government services, shopping, and navigation. Given this diversity, there is no one-size-fits-all framework for how to ethically manage your data. With that in mind, I present seven ethical values for responsible data use.

Genome privacy: challenges, technical approaches to mitigate risk, and ethical considerations in the United States.

Accessing and integrating human genomic data with phenotypes are important for biomedical research. Making genomic data accessible for research purposes, however, must be handled carefully to avoid leakage of sensitive individual information to unauthorized parties and improper use of data. In this article, we focus on data sharing within the scope of data accessibility for research. Current common practices to gain biomedical data access are strictly rule based, without a clear and quantitative measurement of the risk of privacy breaches. In addition, several types of studies require privacy-preserving linkage of genotype and phenotype information across different locations (e.g., genotypes stored in a sequencing facility and phenotypes stored in an electronic health record) to accelerate discoveries. The computer science community has developed a spectrum of techniques for data privacy and confidentiality protection, many of which have yet to be tested on real-world problems. In this article, we discuss clinical, technical, and ethical aspects of genome data privacy and confidentiality in the United States, as well as potential solutions for privacy-preserving genotype-phenotype linkage in biomedical research.

An overview of human genetic privacy.

The study of human genomics is becoming a Big Data science, owing to recent biotechnological advances leading to availability of millions of personal genome sequences, which can be combined with biometric measurements from mobile apps and fitness trackers, and of human behavior data monitored from mobile devices and social media. With increasing research opportunities for integrative genomic studies through data sharing, genetic privacy emerges as a legitimate yet challenging concern that needs to be carefully addressed, not only for individuals but also for their families. In this paper, we present potential genetic privacy risks and relevant ethics and regulations for sharing and protecting human genomics data. We also describe the techniques for protecting human genetic privacy from three broad perspectives: controlled access, differential privacy, and cryptographic solutions.

Regulating genomics in the 21st century: from logos to pathos?

There is currently an important change in the governance of genomics. In the past, much of the regulatory discussion about genomics has focused on issues of risk. Today, a new discussion is evolving that emphasizes the uncertainties involved in the development and diffusion of genomics into society. The increasing importance of emotional language and the focus on trust in the discussion about genomics reflects the attempt to substitute for the shortcomings of logos with ethos and pathos.

Intellectual property strategy in bioinformatics and biochips.

Intellectual property rights are essential in today's technology-driven age. A strong intellectual property protection strategy is crucial in the bioinformatics and biochips technology spaces as monetary and temporal resources are tremendous in finding a blockbuster drug or gene therapy, as well as in deploying advanced biosensor and other medical systems. Current problems and intellectual property practice in the genomic space are presented and analyzed. Various strategy and solutions are proposed to guide bioinformatic and biochip companies in forming an aggressive strategy to protect one's intellectual property and competitive positioning.

Systems theory and the ethics of human enhancement: a framework for NBIC convergence.

Representatives from government and the private sector recommend a major, cooperative initiative directed toward using NBIC (nano-, bio-, info-, and cogno-) technologies for human enhancement. By appropriately seeding the convergence of NBIC domains, they believe that the rate of development can be both accelerated and simultaneously channeled to avoid adverse risk and advance human good. However, to accomplish these goals, leaders of the convergence efforts identified as a major intellectual barrier the "development of a hierarchical architecture for integrating science across many scales, disciplines, and data modalities." Such a holistic framework requires a radical rethinking of the nature of science and engineering, and, beyond this, is also necessary for addressing their normative ethical and societal implications. In the first part of this essay, I consider the claim that a new view of science and engineering is needed. After reviewing the central features of a classical view of science, I consider aspects of the nano-revolution, showing why the classical conception is inappropriate and how a systems-oriented perspective is responsive to the character of this new science. I then consider how both science and engineering are transformed, calling into question older dichotomies between pure and applied domains. With the reworking of this distinction comes opportunities for rethinking the relation between science and the humanities more generally, which is necessary if we are to more appropriately address normative ethical aspects of the convergence initiative. After providing this groundwork for the needed hierarchical architecture, I consider a useful example of how a systems perspective might guide NBIC convergence. In the 1960s-1990s George Engel advocated a systems-theoretic model as an alternative to a more reductionistic "biomedical model" in medicine, and he did it for the exact same reasons as those advocated by the leaders of the NBIC convergence; namely, it embodies a more appropriate notion of science and enables one to address ethical aspects of medicine that were insufficiently addressed in the older model. By reviewing Engel's "biopsychosocial model" we can learn important lessons for developing the needed NBIC framework. I close by extending Engel's model so that it addresses all areas of enhancement envisioned as a part of NBIC convergence, and then identify areas where future research is still needed.

Bioinformatics: perspectives for the future.

I give here a very personal perspective of Bioinformatics and its future, starting by discussing the origin of the term (and area) of bioinformatics and proceeding by trying to foresee the development of related issues, including pattern recognition/data mining, the need to reintegrate biology, the potential of complex networks as a powerful and flexible framework for bioinformatics and the interplay between bio- and neuroinformatics. Human resource formation and market perspective are also addressed. Given the complexity and vastness of these issues and concepts, as well as the limited size of a scientific article and finite patience of the reader, these perspectives are surely incomplete and biased. However, it is expected that some of the questions and trends that are identified will motivate discussions during the IcoBiCoBi round table (with the same name as this article) and perhaps provide a more ample perspective among the participants of that conference and the readers of this text.