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Consensus methods for combining multiple clusterings of chemical structures

Saeed F, Salim N, Abdo A

J Chem Inf Model, 2013 May 24;53(5):1026-34.
PMID: 23581471 DOI: 10.1021/ci300442u

The goal of consensus clustering methods is to find a consensus partition that optimally summarizes an ensemble and improves the quality of clustering compared with single clustering algorithms. In this paper, an enhanced voting-based consensus method was introduced and compared with other consensus clustering methods, including co-association-based, graph-based, and voting-based consensus methods. The MDDR and MUV data sets were used for the experiments and were represented by three 2D fingerprints: ALOGP, ECFP_4, and ECFC_4. The results were evaluated based on the ability of the clustering method to separate active from inactive molecules in each cluster using four criteria: F-measure, Quality Partition Index (QPI), Rand Index (RI), and Fowlkes-Mallows Index (FMI). The experiments suggest that the consensus methods can deliver significant improvements for the effectiveness of chemical structures clustering.

Matched MeSH terms: Informatics/methods*
An analysis of application of health informatics in Traditional Medicine: A review of four Traditional Medicine Systems

Raja Ikram RR, Abd Ghani MK, Abdullah N

Int J Med Inform, 2015 Nov;84(11):988-96.
PMID: 26160148 DOI: 10.1016/j.ijmedinf.2015.05.007

This paper shall first investigate the informatics areas and applications of the four Traditional Medicine systems - Traditional Chinese Medicine (TCM), Ayurveda, Traditional Arabic and Islamic Medicine and Traditional Malay Medicine. Then, this paper shall examine the national informatics infrastructure initiatives in the four respective countries that support the Traditional Medicine systems. Challenges of implementing informatics in Traditional Medicine Systems shall also be discussed.

Matched MeSH terms: Informatics
Fulltext Evaluation and selection of open-source EMR software packages based on integrated AHP and TOPSIS

Zaidan AA, Zaidan BB, Al-Haiqi A, Kiah ML, Hussain M, Abdulnabi M

J Biomed Inform, 2015 Feb;53:390-404.
PMID: 25483886 DOI: 10.1016/j.jbi.2014.11.012

Evaluating and selecting software packages that meet the requirements of an organization are difficult aspects of software engineering process. Selecting the wrong open-source EMR software package can be costly and may adversely affect business processes and functioning of the organization. This study aims to evaluate and select open-source EMR software packages based on multi-criteria decision-making. A hands-on study was performed and a set of open-source EMR software packages were implemented locally on separate virtual machines to examine the systems more closely. Several measures as evaluation basis were specified, and the systems were selected based a set of metric outcomes using Integrated Analytic Hierarchy Process (AHP) and TOPSIS. The experimental results showed that GNUmed and OpenEMR software can provide better basis on ranking score records than other open-source EMR software packages.

Matched MeSH terms: Medical Informatics/methods*
Deep learning for healthcare applications based on physiological signals: A review

Faust O, Hagiwara Y, Hong TJ, Lih OS, Acharya UR

Comput Methods Programs Biomed, 2018 Jul;161:1-13.
PMID: 29852952 DOI: 10.1016/j.cmpb.2018.04.005

BACKGROUND AND OBJECTIVE: We have cast the net into the ocean of knowledge to retrieve the latest scientific research on deep learning methods for physiological signals. We found 53 research papers on this topic, published from 01.01.2008 to 31.12.2017.
METHODS: An initial bibliometric analysis shows that the reviewed papers focused on Electromyogram(EMG), Electroencephalogram(EEG), Electrocardiogram(ECG), and Electrooculogram(EOG). These four categories were used to structure the subsequent content review.
RESULTS: During the content review, we understood that deep learning performs better for big and varied datasets than classic analysis and machine classification methods. Deep learning algorithms try to develop the model by using all the available input.
CONCLUSIONS: This review paper depicts the application of various deep learning algorithms used till recently, but in future it will be used for more healthcare areas to improve the quality of diagnosis.

Matched MeSH terms: Medical Informatics/methods*
A review of automated sleep stage scoring based on physiological signals for the new millennia

Faust O, Razaghi H, Barika R, Ciaccio EJ, Acharya UR

Comput Methods Programs Biomed, 2019 Jul;176:81-91.
PMID: 31200914 DOI: 10.1016/j.cmpb.2019.04.032

BACKGROUND AND OBJECTIVE: Sleep is an important part of our life. That importance is highlighted by the multitude of health problems which result from sleep disorders. Detecting these sleep disorders requires an accurate interpretation of physiological signals. Prerequisite for this interpretation is an understanding of the way in which sleep stage changes manifest themselves in the signal waveform. With that understanding it is possible to build automated sleep stage scoring systems. Apart from their practical relevance for automating sleep disorder diagnosis, these systems provide a good indication of the amount of sleep stage related information communicated by a specific physiological signal.
METHODS: This article provides a comprehensive review of automated sleep stage scoring systems, which were created since the year 2000. The systems were developed for Electrocardiogram (ECG), Electroencephalogram (EEG), Electrooculogram (EOG), and a combination of signals.
RESULTS: Our review shows that all of these signals contain information for sleep stage scoring.
CONCLUSIONS: The result is important, because it allows us to shift our research focus away from information extraction methods to systemic improvements, such as patient comfort, redundancy, safety and cost.

Matched MeSH terms: Medical Informatics
The m-Health revolution: Exploring perceived benefits of WhatsApp use in clinical practice

Ganasegeran K, Renganathan P, Rashid A, Al-Dubai SA

Int J Med Inform, 2017 01;97:145-151.
PMID: 27919374 DOI: 10.1016/j.ijmedinf.2016.10.013

BACKGROUND: The dawn of m-Health facilitates new horizons of professional communication through WhatsApp, allowing health professionals to interact fast and efficiently for effective patient management. This preliminary study aimed to investigate perceived benefits, if any, of WhatsApp use across general medical and emergency teams during clinical practice in Malaysia.
METHODS: A cross-sectional study was conducted in a universal sample of 307 health professionals comprising of nurses, medical assistants, medical residents, medical officers and physicians across medical and casualty departments in a Malaysian public hospital. The self-administered questionnaire consisted of items on socio-demographics, WhatsApp usage characteristics and the type of communication events during clinical practice.
RESULTS: The majority of respondents (68.4%) perceived WhatsApp as beneficial during clinical practice. In multivariate analysis, perceived benefits was significantly higher amongst the clinical management group (aOR=2.6, 95% CI 1.5-4.6, p=0.001), those using WhatsApp for >12months (aOR=1.7, 95% CI 1.0-3.0, p=0.047), those receiving response ≤15min to a new communication (aOR=1.9, 95% CI 1.1-3.2, p=0.017), and frequent information giving events (aOR=2.4, 95% CI 1.2-4.8, p=0.016).
CONCLUSION: Perceived benefits of WhatsApp use in clinical practice was significantly associated with usage characteristics and type of communication events. This study lays the foundation for quality improvement innovations in patient management delivered through m-Health technology.

Matched MeSH terms: Medical Informatics*
Fulltext Classification of forensic autopsy reports through conceptual graph-based document representation model

Mujtaba G, Shuib L, Raj RG, Rajandram R, Shaikh K, Al-Garadi MA

J Biomed Inform, 2018 06;82:88-105.
PMID: 29738820 DOI: 10.1016/j.jbi.2018.04.013

Text categorization has been used extensively in recent years to classify plain-text clinical reports. This study employs text categorization techniques for the classification of open narrative forensic autopsy reports. One of the key steps in text classification is document representation. In document representation, a clinical report is transformed into a format that is suitable for classification. The traditional document representation technique for text categorization is the bag-of-words (BoW) technique. In this study, the traditional BoW technique is ineffective in classifying forensic autopsy reports because it merely extracts frequent but discriminative features from clinical reports. Moreover, this technique fails to capture word inversion, as well as word-level synonymy and polysemy, when classifying autopsy reports. Hence, the BoW technique suffers from low accuracy and low robustness unless it is improved with contextual and application-specific information. To overcome the aforementioned limitations of the BoW technique, this research aims to develop an effective conceptual graph-based document representation (CGDR) technique to classify 1500 forensic autopsy reports from four (4) manners of death (MoD) and sixteen (16) causes of death (CoD). Term-based and Systematized Nomenclature of Medicine-Clinical Terms (SNOMED CT) based conceptual features were extracted and represented through graphs. These features were then used to train a two-level text classifier. The first level classifier was responsible for predicting MoD. In addition, the second level classifier was responsible for predicting CoD using the proposed conceptual graph-based document representation technique. To demonstrate the significance of the proposed technique, its results were compared with those of six (6) state-of-the-art document representation techniques. Lastly, this study compared the effects of one-level classification and two-level classification on the experimental results. The experimental results indicated that the CGDR technique achieved 12% to 15% improvement in accuracy compared with fully automated document representation baseline techniques. Moreover, two-level classification obtained better results compared with one-level classification. The promising results of the proposed conceptual graph-based document representation technique suggest that pathologists can adopt the proposed system as their basis for second opinion, thereby supporting them in effectively determining CoD.

Matched MeSH terms: Medical Informatics/methods*
Fulltext Development of a Personalized Mobile Mental Health Intervention for Workplace Cyberbullying Among Health Practitioners: Protocol for a Mixed Methods Study

Kim YJ, Qian L, Aslam MS

JMIR Res Protoc, 2020 Nov 20;9(11):e23112.
PMID: 33216000 DOI: 10.2196/23112

BACKGROUND: Workplace cyberbullying harms the psychological and social functioning of professionals working in an organization and may decrease the productivity and efficiency of daily life tasks. A recent study on trainee doctors across 8 different United Kingdom National Health Service trusts found health issues and job dissatisfaction in people who have experienced workplace cyberbullying. This disabling effect is even more noticeable in low-socioeconomic communities within low-income countries. In Malaysia, there is a need to create a personalized mobile mental health intervention program for health care professionals. These programs should be directed to prevent and decrease psychosocial issues and enhance coordination among health care professionals to solve health issues in the community.
OBJECTIVE: Our main objective is to study the pre-effects and posteffects of the Personalized Mobile Mental Health Intervention (PMMH-I) for workplace cyberbullying in public and private hospitals in Malaysia.
METHODS: A hospital-based multimethod multi-analytic evidential approach is proposed, involving social and psychological health informatics. The project has been subdivided into 3 stages, starting with Phase 1, a prevalence study, followed by exploratory studies. Phase 2 consists of a quasi-experimental design, whereas the development of a prototype and their testing will be proposed in Phase 3. Each stage includes the use of quantitative and qualitative methods (mixed-method program), using SPSS (version 26.0; IBM Corp) and Stata (version 16.1; StataCorp) as tools for quantitative research, and NVivo (version 1.0; QSR International) and Atlas.ti (version 9.0.16; ATLAS.ti Scientific Software Development GmbH) for qualitative research.
RESULTS: The results of this study will determine the pre- and posteffectiveness of an integrated PMMH-I for health care professionals. The prototype system platform will be developed and implemented in a public and private hospital. Results from Phase 1 will be published in 2021, followed by the implementation of Phase 2 in subsequent years.
CONCLUSIONS: This study will provide evidence and guidance regarding the implementation of a personalized mobile mental health intervention for health care professionals into routine public and private hospitals to enhance communication and resolve conflicts.
INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/23112.

Matched MeSH terms: Medical Informatics
Proposing an ecologically viable and economically sound farming system using a matrix-based geo-informatics approach

Senanayake S, Pradhan B, Huete A, Brennan J

Sci Total Environ, 2021 Nov 10;794:148788.
PMID: 34323751 DOI: 10.1016/j.scitotenv.2021.148788

Healthy farming systems play a vital role in improving agricultural productivity and sustainable food production. The present study aimed to propose an efficient framework to evaluate ecologically viable and economically sound farming systems using a matrix-based analytic hierarchy process (AHP) and weighted linear combination method with geo-informatics tools. The proposed framework has been developed and tested in the Central Highlands of Sri Lanka. Results reveal that more than 50% of farming systems demonstrated moderate status in terms of ecological and economic aspects. However, two vulnerable farming systems on the western slopes of the Central Highlands, named WL1a and WM1a, were identified as very poor status. These farming systems should be a top priority for restoration planning and soil conservation to prevent further deterioration. Findings indicate that a combination of ecologically viable (nine indicators) and economical sound (four indicators) criteria are a practical method to scrutinize farming systems and decision making on soil conservation and sustainable land management. In addition, this research introduces a novel approach to delineate the farming systems based on agro-ecological regions and cropping areas using geo-informatics technology. This framework and methodology can be employed to evaluate the farming systems of other parts of the country and elsewhere to identify ecologically viable and economically sound farming systems concerning soil erosion hazards. The proposed approach addresses a new dimension of the decision-making process by evaluating the farming systems relating to soil erosion hazards and suggests introducing policies on priority-based planning for conservation with low-cost strategies for sustainable land management.

Matched MeSH terms: Informatics
Intelligent healthcare information assistant: towards agent-based healthcare knowledge management

Hashmi ZI, Abidi SS, Cheah YN

Stud Health Technol Inform, 2002;90:601-5.
PMID: 15460764

Initiatives in healthcare knowledge management have provided some interesting solutions for the implementation of large-scale information repositories vis-à-vis the implementation of Healthcare Enterprise Memories (HEM). In this paper, we present an agent-based Intelligent Healthcare Information Assistant (IHIA) for dynamic information gathering, filtering and adaptation from a HEM comprising an amalgamation of (i) databases storing empirical knowledge, (ii) case-bases storing experiential knowledge, (iii) scenario-bases storing tacit knowledge and (iv) document-bases storing explicit knowledge. The featured work leverages intelligent agents and medical ontologies for autonomous HEM-wide navigation, approximate content matching, inter- and intra-repositories content correlation and information adaptation to meet the user's information request. We anticipate that the use of IHIA will empower healthcare stakeholders to actively communicate with an 'information/knowledge-rich' HEM and will be able to retrieve with ease 'useful' task-specific information via the presentation of cognitively intuitive queries.

Matched MeSH terms: Medical Informatics*
A novel strategy for load balancing of distributed medical applications

Logeswaran R, Chen LC

J Med Syst, 2012 Apr;36(2):483-90.
PMID: 20703702 DOI: 10.1007/s10916-010-9493-0

Current trends in medicine, specifically in the electronic handling of medical applications, ranging from digital imaging, paperless hospital administration and electronic medical records, telemedicine, to computer-aided diagnosis, creates a burden on the network. Distributed Service Architectures, such as Intelligent Network (IN), Telecommunication Information Networking Architecture (TINA) and Open Service Access (OSA), are able to meet this new challenge. Distribution enables computational tasks to be spread among multiple processors; hence, performance is an important issue. This paper proposes a novel approach in load balancing, the Random Sender Initiated Algorithm, for distribution of tasks among several nodes sharing the same computational object (CO) instances in Distributed Service Architectures. Simulations illustrate that the proposed algorithm produces better network performance than the benchmark load balancing algorithms-the Random Node Selection Algorithm and the Shortest Queue Algorithm, especially under medium and heavily loaded conditions.

Matched MeSH terms: Medical Informatics Applications*
Fulltext Development of a Search Strategy for an Evidence Based Retrieval Service

Ho GJ, Liew SM, Ng CJ, Hisham Shunmugam R, Glasziou P

PLoS One, 2016;11(12):e0167170.
PMID: 27935993 DOI: 10.1371/journal.pone.0167170

BACKGROUND: Physicians are often encouraged to locate answers for their clinical queries via an evidence-based literature search approach. The methods used are often not clearly specified. Inappropriate search strategies, time constraint and contradictory information complicate evidence retrieval.
AIMS: Our study aimed to develop a search strategy to answer clinical queries among physicians in a primary care setting.
METHODS: Six clinical questions of different medical conditions seen in primary care were formulated. A series of experimental searches to answer each question was conducted on 3 commonly advocated medical databases. We compared search results from a PICO (patients, intervention, comparison, outcome) framework for questions using different combinations of PICO elements. We also compared outcomes from doing searches using text words, Medical Subject Headings (MeSH), or a combination of both. All searches were documented using screenshots and saved search strategies.
RESULTS: Answers to all 6 questions using the PICO framework were found. A higher number of systematic reviews were obtained using a 2 PICO element search compared to a 4 element search. A more optimal choice of search is a combination of both text words and MeSH terms. Despite searching using the Systematic Review filter, many non-systematic reviews or narrative reviews were found in PubMed. There was poor overlap between outcomes of searches using different databases. The duration of search and screening for the 6 questions ranged from 1 to 4 hours.
CONCLUSION: This strategy has been shown to be feasible and can provide evidence to doctors' clinical questions. It has the potential to be incorporated into an interventional study to determine the impact of an online evidence retrieval system.

Matched MeSH terms: Medical Informatics/methods; Medical Informatics/standards; Medical Informatics/statistics & numerical data
A personalised Healthcare Information Delivery System: pushing customised healthcare information over the WWW

Abidi SS, Goh A

Stud Health Technol Inform, 2000;77:663-7.
PMID: 11187636

Easier and focused access to healthcare information can empower individuals to make 'informed' choices and judgements about personal health maintenance. To achieve 'optimum' patient empowerment, we need to re-evaluate and potentially re-design the processes of healthcare information delivery. Our suggestion is that healthcare information should be personalised according to each individual's healthcare needs and it should be pro-actively delivered, i.e. pushed towards the individual. We present an intelligent Personalised Healthcare Information Delivery Systems that aims to enhance patient empowerment by pro-actively pushing customised, based on one's Electronic Medical Record, health maintenance information via the WWW.

Matched MeSH terms: Medical Informatics Computing*
Computerized segmentation and measurement of chronic wound images

Ahmad Fauzi MF, Khansa I, Catignani K, Gordillo G, Sen CK, Gurcan MN

Comput Biol Med, 2015 May;60:74-85.
PMID: 25756704 DOI: 10.1016/j.compbiomed.2015.02.015

An estimated 6.5 million patients in the United States are affected by chronic wounds, with more than US$25 billion and countless hours spent annually for all aspects of chronic wound care. There is a need for an intelligent software tool to analyze wound images, characterize wound tissue composition, measure wound size, and monitor changes in wound in between visits. Performed manually, this process is very time-consuming and subject to intra- and inter-reader variability. In this work, our objective is to develop methods to segment, measure and characterize clinically presented chronic wounds from photographic images. The first step of our method is to generate a Red-Yellow-Black-White (RYKW) probability map, which then guides the segmentation process using either optimal thresholding or region growing. The red, yellow and black probability maps are designed to handle the granulation, slough and eschar tissues, respectively; while the white probability map is to detect the white label card for measurement calibration purposes. The innovative aspects of this work include defining a four-dimensional probability map specific to wound characteristics, a computationally efficient method to segment wound images utilizing the probability map, and auto-calibration of wound measurements using the content of the image. These methods were applied to 80 wound images, captured in a clinical setting at the Ohio State University Comprehensive Wound Center, with the ground truth independently generated by the consensus of at least two clinicians. While the mean inter-reader agreement between the readers varied between 67.4% and 84.3%, the computer achieved an average accuracy of 75.1%.

Matched MeSH terms: Medical Informatics/methods
Informatics and Computational Approaches for the Discovery and Optimization of Natural Product-Inspired Inhibitors of the SARS-CoV-2 2'-O-Methyltransferase

Hanna GS, Benjamin MM, Choo YM, De R, Schinazi RF, Nielson SE, et al.

J Nat Prod, 2024 Feb 23;87(2):217-227.
PMID: 38242544 DOI: 10.1021/acs.jnatprod.3c00875

The urgent need for new classes of orally available, safe, and effective antivirals─covering a breadth of emerging viruses─is evidenced by the loss of life and economic challenges created by the HIV-1 and SARS-CoV-2 pandemics. As frontline interventions, small-molecule antivirals can be deployed prophylactically or postinfection to control the initial spread of outbreaks by reducing transmissibility and symptom severity. Natural products have an impressive track record of success as prototypic antivirals and continue to provide new drugs through synthesis, medicinal chemistry, and optimization decades after discovery. Here, we demonstrate an approach using computational analysis typically used for rational drug design to identify and develop natural product-inspired antivirals. This was done with the goal of identifying natural product prototypes to aid the effort of progressing toward safe, effective, and affordable broad-spectrum inhibitors of Betacoronavirus replication by targeting the highly conserved RNA 2'-O-methyltransferase (2'-O-MTase). Machaeriols RS-1 (7) and RS-2 (8) were identified using a previously outlined informatics approach to first screen for natural product prototypes, followed by in silico-guided synthesis. Both molecules are based on a rare natural product group. The machaeriols (3-6), isolated from the genus Machaerium, endemic to Amazonia, inhibited the SARS-CoV-2 2'-O-MTase more potently than the positive control, Sinefungin (2), and in silico modeling suggests distinct molecular interactions. This report highlights the potential of computationally driven screening to leverage natural product libraries and improve the efficiency of isolation or synthetic analog development.

Matched MeSH terms: Informatics
Economics of health informatics in developing countries

Hébert RJ

Stud Health Technol Inform, 2011;164:162-7.
PMID: 21335705

Health Informatics (HI) has become a world wide issue since 2005 when the WHO Health Metrics Network (HMN) was formed to encourage all of the developing countries (151) to get started in eHealth. Prior to this HMN initiative the only countries with HI in place were the developed countries (40) and a few developing countries (Jamaica, Malaysia, etc.) that were just getting started in HI with a very limited number of applications compared to the developed countries. This paper suggests that much of the experience in HI gained in the developed countries can be shared with the developing countries as 'lessons learnt' - as long as the issue of economics is kept front and foremost in the planning.

Matched MeSH terms: Medical Informatics/economics*
Fulltext Translating Evidence Into Practice via Social Media: A Mixed-Methods Study

Maloney S, Tunnecliff J, Morgan P, Gaida JE, Clearihan L, Sadasivan S, et al.

J Med Internet Res, 2015 Oct 26;17(10):e242.
PMID: 26503129 DOI: 10.2196/jmir.4763

BACKGROUND: Approximately 80% of research evidence relevant to clinical practice never reaches the clinicians delivering patient care. A key barrier for the translation of evidence into practice is the limited time and skills clinicians have to find and appraise emerging evidence. Social media may provide a bridge between health researchers and health service providers.
OBJECTIVE: The aim of this study was to determine the efficacy of social media as an educational medium to effectively translate emerging research evidence into clinical practice.
METHODS: The study used a mixed-methods approach. Evidence-based practice points were delivered via social media platforms. The primary outcomes of attitude, knowledge, and behavior change were assessed using a preintervention/postintervention evaluation, with qualitative data gathered to contextualize the findings.
RESULTS: Data were obtained from 317 clinicians from multiple health disciplines, predominantly from the United Kingdom, Australia, the United States, India, and Malaysia. The participants reported an overall improvement in attitudes toward social media for professional development (P

Matched MeSH terms: Medical Informatics
Introducing SNOMED CT to cardiology, from Malaysia

Sulaiman IM, Sheikh Ahmad MK, Bouzekri K, Ismail D

Eur Heart J, 2015 Jul 7;36(26):1636-9.
PMID: 26366446
Matched MeSH terms: Medical Informatics
Classification of antecedents towards safety use of health information technology: A systematic review

Salahuddin L, Ismail Z

Int J Med Inform, 2015 Nov;84(11):877-91.
PMID: 26238706 DOI: 10.1016/j.ijmedinf.2015.07.004

This paper provides a systematic review of safety use of health information technology (IT). The first objective is to identify the antecedents towards safety use of health IT by conducting systematic literature review (SLR). The second objective is to classify the identified antecedents based on the work system in Systems Engineering Initiative for Patient Safety (SEIPS) model and an extension of DeLone and McLean (D&M) information system (IS) success model.

Matched MeSH terms: Medical Informatics
Hidden Concepts in the History and Philosophy of Origins-of-Life Studies: a Workshop Report

Mariscal C, Barahona A, Aubert-Kato N, Aydinoglu AU, Bartlett S, Cárdenas ML, et al.

Orig Life Evol Biosph, 2019 Sep;49(3):111-145.
PMID: 31399826 DOI: 10.1007/s11084-019-09580-x

In this review, we describe some of the central philosophical issues facing origins-of-life research and provide a targeted history of the developments that have led to the multidisciplinary field of origins-of-life studies. We outline these issues and developments to guide researchers and students from all fields. With respect to philosophy, we provide brief summaries of debates with respect to (1) definitions (or theories) of life, what life is and how research should be conducted in the absence of an accepted theory of life, (2) the distinctions between synthetic, historical, and universal projects in origins-of-life studies, issues with strategies for inferring the origins of life, such as (3) the nature of the first living entities (the "bottom up" approach) and (4) how to infer the nature of the last universal common ancestor (the "top down" approach), and (5) the status of origins of life as a science. Each of these debates influences the others. Although there are clusters of researchers that agree on some answers to these issues, each of these debates is still open. With respect to history, we outline several independent paths that have led to some of the approaches now prevalent in origins-of-life studies. These include one path from early views of life through the scientific revolutions brought about by Linnaeus (von Linn.), Wöhler, Miller, and others. In this approach, new theories, tools, and evidence guide new thoughts about the nature of life and its origin. We also describe another family of paths motivated by a" circularity" approach to life, which is guided by such thinkers as Maturana & Varela, Gánti, Rosen, and others. These views echo ideas developed by Kant and Aristotle, though they do so using modern science in ways that produce exciting avenues of investigation. By exploring the history of these ideas, we can see how many of the issues that currently interest us have been guided by the contexts in which the ideas were developed. The disciplinary backgrounds of each of these scholars has influenced the questions they sought to answer, the experiments they envisioned, and the kinds of data they collected. We conclude by encouraging scientists and scholars in the humanities and social sciences to explore ways in which they can interact to provide a deeper understanding of the conceptual assumptions, structure, and history of origins-of-life research. This may be useful to help frame future research agendas and bring awareness to the multifaceted issues facing this challenging scientific question.

Matched MeSH terms: Informatics/history*

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