Human Olfactory Receptor Comparative Sequence Assessments from the Genome

We present a review of the results of research to identify olfactory receptor gene sequences from the Human Genome. This effort began soon after the publication of the first draft of the genome. Subsequent publications of the genome have allowed the evolution of OR gene identification with improved accuracy. We performed a comprehensive sequence analysis to identify 100% sequence matches, as well as partial matches by performing the same sequence matching step against random partial regions of sequences. Only sequences supplied to us from the groups that mined the olfactory receptor sequences from the genome or were available online were used in the analysis. The results are publicly available at https:// ordb.biotech.ttu.edu/ORDB/info/humanorseqanal. We also performed a similar assessment of mouse olfactory receptor sequences from two groups that assessed the mouse genome, publicly available at https://ordb.biotech.ttu.edu/ORDB/info/mouseorseqanal. Both resources are linked through a list of potential orthologs between the two species’ receptor sequences. This review also contains a discussion of nomenclatures of these genes and the resources as information dissemination portals.

Read More About This Article: 10.31031/OABB.2024.03.000571

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Enhancing Learning with ChatGPT: A Transformative Educational Companion

In recent years, the integration of Artificial Intelligence (AI) technologies into educational settings has opened up new possibilities for personalized and interactive learning experiences. Among these technologies, ChatGPT, an advanced language model developed by OpenAI, has emerged as a promising educational companion. ChatGPT utilizes Natural Language Processing (NLP) algorithms to engage in conversational interactions, provide feedback, and deliver personalized learning materials. This academic review explores the potential of leveraging ChatGPT as a transformative educational companion, examining its applications, benefits, challenges, and implications for teaching and learning.

Applications of ChatGPT in Education

ChatGPT offers a wide range of applications in education, ranging from providing instant feedback on student responses to facilitating interactive learning experiences. As a conversational agent, ChatGPT can engage students in dialogues on various topics, clarify concepts, and answer questions in real-time. Additionally, ChatGPT can generate personalized learning materials, such as summaries, quizzes, and study guides, tailored to individual students’ needs and preferences. Furthermore, ChatGPT can assist educators in tasks such as lesson planning, content creation, and assessment design, enhancing instructional efficiency and effectiveness.

 Read More About This Article: 10.31031/OABB.2024.03.000570

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Mining Online Author’s Publication to Report the Core Research Domain with PubMed MeSH Terms: a Systematic Review for a Journal- Crimson Publishers

Mining Online Author’s Publication to Report the Core Research Domain with PubMed MeSH 

Terms: a Systematic Review for a Journal by Tsair Wei Chien in Open Access Biostatistics & 

Bioinformatic: Crimson Publishers_ Bioinformatics Open Access Journals

Background: Identifying an author’s research domain (RD) using MeSH (Medical Subject Headings)
terms is essential for a journal’s development and its readership, but no journal uses mining online 
methods or social network analysis (SNA) to extract journal publication information to report an 
author’s contributions.


Objective: To select prestigious authors and papers that have contributed most to a journal, 
we retrospectively (1) calculated an SCI (Science Citation Index) journal’s most recent impact 
factors (IF) and (2) used graphical representations that include MeSH terms of RDs for authors 
and journals.


Methods: We collected 2,053 papers published between July 1, 1999, and April 3, 2017, in the 
Journal of Medical Internet Research (JMIR) and cited by 673 journals, for which we also 
collected annual IFs for 394 SCI journals, including the JMIR. The prestigious authors and JMIR 
papers based on the weight of the 5-year SCI IFs from 394 cited-by papers in 2015. The JMIR 
core aims and scope are presented using major MeSH terms based on their corresponding 
average weighted scores. Social network analysis was used to create a graphical RD pattern for 
JMIR, and its prestigious papers and authors.


Results: All JMIR 5-year IFs have not been less than 2.9 for the past 14 years. The authors who 
contributed most to JMIR in a number of publications and weighted citations are Gunther 
Eysenbach and My Hua. Their cohesion measures (ranging from 0 to 1.0) to JMIR are 34% and 
5.7%, respectively. The highest prestige weighted contribution among papers published in JMIR 
is the one (PMID: 23567935 /DOI: 10.2196/jmir.2324) with a cohesion measure of 4.5%.


Conclusion: An author’s research domain is required with an essential and graphical 
presentation along with the author’s submission to the target journal. Journal editors also 
look forward to evaluating an author’s research domain and the submitted paper’s cohesion 
measure for the journal.


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