Biomanufacturing Technologies for Engineering Biology

Engineering Biology seeks to apply engineering principles to design, modify, and produce customized biological components and systems. The recent advent of tools such as the CRISPR/Cas9 system for gene editing and gene regulation has sharply accelerated development in this exciting field. However, several challenges need to be addressed in order to transition laboratory-scale results to commercial-scale solutions. This report identifies emerging platform technologies that, if matured, will accelerate the growth in the rapidly changing field of Engineering Biology. The conclusions in the report are intended to guide stakeholders from government, industry and academia as they seek to further develop innovations in this field.The technologies that clearly met the selection criteria include: • The key platform technology—Standardized Verified and Tractable Host Cells or Strains for Biomanufacturing—will provide industries with host cells and strains that are amenable to engineering for scale-up or scale-out. The standardized and verified nature of these hosts will streamline regulatory processes and significantly de-risk aspects of the biomanufacturing process. • Several enabling tools are needed to fully realize the potential offered by the development of tractable host cells or strains. These tools will also enable more rapid Design-Build-Test-Learn (DBTL) cycles, which is critical for the development of new host cells or strains. These tools include: (i) High Throughput Omics; (ii) Low-Cost and Error Free DNA Elements and DNA Assembly; and (iii) Efficient, Host-Neutral Gene Editing.National Science Foundation, Grant No. 1552534https://deepblue.lib.umich.edu/bitstream/2027.42/144782/1/EngineeringBiology_Final.pdfDescription of EngineeringBiology_Final.pdf : Repor

Long term productivity and collaboration in information science

This is an accepted manuscript of an article published by Springer in Scientometrics on 02/07/2016, available online: https://doi.org/10.1007/s11192-016-2061-8 The accepted version of the publication may differ from the final published version.Funding bodies have tended to encourage collaborative research because it is generally more highly cited than sole author research. But higher mean citation for collaborative articles does not imply collaborative researchers are in general more research productive. This article assesses the extent to which research productivity varies with the number of collaborative partners for long term researchers within three Web of Science subject areas: Information Science & Library Science, Communication and Medical Informatics. When using the whole number counting system, researchers who worked in groups of 2 or 3 were generally the most productive, in terms of producing the most papers and citations. However, when using fractional counting, researchers who worked in groups of 1 or 2 were generally the most productive. The findings need to be interpreted cautiously, however, because authors that produce few academic articles within a field may publish in other fields or leave academia and contribute to society in other ways

Toward disease-specific therapies in mind-body cancer research: reverse engineering, epigenetic feedback and in vitro/ in vivo combination protocols

Although we have significant experimental evidence demonstrating that specific meditation forms correlate with particular effects on biological targets, mind-body  therapeutic applications are still very rudimentary and poorly standardized, consisting of little more than exercises designed to trigger a parasympathetic response.  If the sole physiological effect of meditation were related to the relaxation response, then indeed most forms of meditation would be expected to work in similar ways and achieve similar results. But as we have explored in a previous panel discussion anchored by Michael Persinger and his group [Bajpai et al., Journal of Nonlocality, II-2, 2013], the convergence of photobiology  and qigong experimental research  indicates that specific brainwave patterns correlate with specific biophoton emission frequencies, microtubule conformational states  and biological effects, both at the level of the operator’s body and in remote targets. Of greatest clinical  interest is the ability of focused intent to produce target-specific, directional effects, while leaving control samples unaffected – a feature that has been documented by over a hundred  in vitro and in vivo controlled qigong experiments and corroborated by several hundred  Random Event Generator (REG) studies conducted at Princeton and other university labs.  While the physical modeling of such remote effects is still speculative, the potential applications are sufficiently intriguing to warrant an empirical  leap ahead of the theoretical staging.  If cancer is “a disease of geometry” due to a  “misregulation of the field of information that orchestrates individual cells’ activities towards normal anatomy”, as Chernet and Levin argue [Chernet and Levin, J Clin Exp Oncol 2013, S1], could we find a way to design  and calibrate specific meditation forms to predictably achieve intended electromagnetic effects  at a biological target (such as  a tumor)?  The present paper proposes a general approach that might  take us a step closer to tailoring such targeted mind-body interventions  through the use of reverse engineering, rapid-expression epigenetic feedback and an in vitro/ in vivo combination protocol

Not all international collaboration is beneficial: The Mendeley readership and citation impact of biochemical research collaboration

This is an accepted manuscript of an article published by Wiley Blackwell in Journal of the Association for Information Science and Technology on 13/05/2015, available online: https://doi.org/10.1002/asi.23515 The accepted version of the publication may differ from the final published version.Biochemistry is a highly funded research area that is typified by large research teams and is important for many areas of the life sciences. This article investigates the citation impact and Mendeley readership impact of biochemistry research from 2011 in the Web of Science according to the type of collaboration involved. Negative binomial regression models are used that incorporate, for the first time, the inclusion of specific countries within a team. The results show that, holding other factors constant, larger teams robustly associate with higher impact research, but including additional departments has no effect and adding extra institutions tends to reduce the impact of research. Although international collaboration is apparently not advantageous in general, collaboration with the USA, and perhaps also with some other countries, seems to increase impact. In contrast, collaborations with some other nations associate with lower impact, although both findings could be due to factors such as differing national proportions of excellent researchers. As a methodological implication, simpler statistical models would have found international collaboration to be generally beneficial and so it is important to take into account specific countries when examining collaboration

Scientific Productions and Authorship Patterns of Top Ten Iranian Scientists

Using bibliographic records from the Social Science Citation Index, Science Citation Index, and Arts & Humanities Index, this paper tries to give a complete view of the characteristics of top ten Iranian authors during 1990-2007 according to their authorship pattern. Findings revealed that during 1990-2007 a total of 2650 articles were written by top ten Iranian authors. Findings showed that M. Shamsipour with 463 articles is the most productive scientist of Iran during the studied period. M. M. Heravi with 365 articles and M. Ganjali with 283 articles appeared in the table at second and third positions, respectively. Findings revealed that overwhelmingly the majority of articles (97/69%) written by Iranian top authors are the result of collaborative works and the authors are highly inclined towards collaborative rather than non-collaborative research. There was a remarkable relationship between co-authorship and number of citations. More-than-three-author articles received the most number of citations. On the other hand, it seems that international collaboration of Iranian top authors is not significant

The Human Phenotype Ontology in 2024: phenotypes around the world

The Human Phenotype Ontology (HPO) is a widely used resource that comprehensively organizes and defines the phenotypic features of human disease, enabling computational inference and supporting genomic and phenotypic analyses through semantic similarity and machine learning algorithms. The HPO has widespread applications in clinical diagnostics and translational research, including genomic diagnostics, gene-disease discovery, and cohort analytics. In recent years, groups around the world have developed translations of the HPO from English to other languages, and the HPO browser has been internationalized, allowing users to view HPO term labels and in many cases synonyms and definitions in ten languages in addition to English. Since our last report, a total of 2239 new HPO terms and 49235 new HPO annotations were developed, many in collaboration with external groups in the fields of psychiatry, arthrogryposis, immunology and cardiology. The Medical Action Ontology (MAxO) is a new effort to model treatments and other measures taken for clinical management. Finally, the HPO consortium is contributing to efforts to integrate the HPO and the GA4GH Phenopacket Schema into electronic health records (EHRs) with the goal of more standardized and computable integration of rare disease data in EHRs

The Human Phenotype Ontology in 2024: phenotypes around the world

\ua9 The Author(s) 2023. Published by Oxford University Press on behalf of Nucleic Acids Research. The Human Phenotype Ontology (HPO) is a widely used resource that comprehensively organizes and defines the phenotypic features of human disease, enabling computational inference and supporting genomic and phenotypic analyses through semantic similarity and machine learning algorithms. The HPO has widespread applications in clinical diagnostics and translational research, including genomic diagnostics, gene-disease discovery, and cohort analytics. In recent years, groups around the world have developed translations of the HPO from English to other languages, and the HPO browser has been internationalized, allowing users to view HPO term labels and in many cases synonyms and definitions in ten languages in addition to English. Since our last report, a total of 2239 new HPO terms and 49235 new HPO annotations were developed, many in collaboration with external groups in the fields of psychiatry, arthrogryposis, immunology and cardiology. The Medical Action Ontology (MAxO) is a new effort to model treatments and other measures taken for clinical management. Finally, the HPO consortium is contributing to efforts to integrate the HPO and the GA4GH Phenopacket Schema into electronic health records (EHRs) with the goal of more standardized and computable integration of rare disease data in EHRs

A bibliometric classificatory approach for the study and assessment of research performance at the individual level: the effects of age on productivity and impact

This paper sets forth a general methodology for conducting bibliometric analyses at the micro level. It combines several indicators grouped into three factors or dimensions which characterize different aspects of scientific performance. Different profiles or “classes” of scientists are described according to their research performance in each dimension. A series of results based on the findings from the application of this methodology to the study of CSIC scientists in Spain in three thematic areas are presented. Special emphasis is made on the identification and description of top scientists from structural and bibliometric perspectives. The effects of age on the productivity and impact of the different classes of scientists are analyzed. The classificatory approach proposed herein may prove a useful tool in support of research assessment at the individual level and for exploring potential determinants of research success.Peer reviewe

The Human Phenotype Ontology in 2024: phenotypes around the world.

The Human Phenotype Ontology (HPO) is a widely used resource that comprehensively organizes and defines the phenotypic features of human disease, enabling computational inference and supporting genomic and phenotypic analyses through semantic similarity and machine learning algorithms. The HPO has widespread applications in clinical diagnostics and translational research, including genomic diagnostics, gene-disease discovery, and cohort analytics. In recent years, groups around the world have developed translations of the HPO from English to other languages, and the HPO browser has been internationalized, allowing users to view HPO term labels and in many cases synonyms and definitions in ten languages in addition to English. Since our last report, a total of 2239 new HPO terms and 49235 new HPO annotations were developed, many in collaboration with external groups in the fields of psychiatry, arthrogryposis, immunology and cardiology. The Medical Action Ontology (MAxO) is a new effort to model treatments and other measures taken for clinical management. Finally, the HPO consortium is contributing to efforts to integrate the HPO and the GA4GH Phenopacket Schema into electronic health records (EHRs) with the goal of more standardized and computable integration of rare disease data in EHRs