Addresses of All Authors

Matthew Cserhati

2615C Muscatel Ave

Rosemead, CA, 91770

United States

Author's Biography

Matthew Cserhati has published 45 technical level articles in creation science. His specialty is bioinformatics and molecular baraminology. He has also led a team that assembled the whole genome sequence of Neanderthal and Denisovan. He has a PhD in bioinformatics, a BSc in software development, and an MA in theology. He has taught several college level courses on bioinformatics.

Presentation Type

Abstract Presentation



There are 24,165 organelle DNA sequences at the Organelle Genome webpage at the NCBI website, as of June 19, 2022. Of these, 14,799 are mitochondrial genomes and 8,050 are chloroplast genomes. Since organelle genomes are very small and very abundant within the cell, they are easy to isolate and sequence. This means that there is a very large number of organelle genome data available for baraminologists to explore and analyze. Using organelle genomes is a quick way to map a large number of species to their respective baramins in preliminary baraminology studies.

The first mitochondrial DNA (mtDNA) studies in turtles were several decades ago (Robinson, 1997), but were limited in scope. Since then, further molecular baraminology analyses have taken place, classifying species into their respective baramins using more developed bioinformatics tools. These include the alignment of the mitochondrial genomes of different species to measure sequence similarity between those species (O’Micks, 2018; Cserhati and Carter, 2020). However, these tools had to be run step by step manually, taking a lot of time.

A novel software to help organelle genome-based baraminology studies

In this paper, I would present a new software that is capable of automatically aligning organelle genome sequences in order to measure sequence similarity and cluster target species into putative baramins. As input, the script takes a list of species names and their corresponding NCBI accession numbers and an estimate of the number of putative baramins expected from the data. With a single command line run, the script does the following things:

  • downloads the organelle genome sequences from NCBI
  • performs an all-versus-all sequence comparison between all of the organelle genomes
  • calculates a symmetric sequence similarity matrix
  • visualizes this sequence similarity matrix in a heat map
  • predicts the membership of the putative baramins
  • calculates other statistical values for each baramin and creates a baraminic tree for each baramin
  • creates an elbow and two-dimensional MDS plot to visualize species relationships between baramins

Advances in molecular baraminology

This software can make baraminology research more efficient by running the entire organelle genome analysis automatically instead of running the steps listed above manually. All the researcher has to do is prepare a simple text file with species names and accession numbers, and run a single command. Even non-bioinformaticians can run the script with little training in Linux.

Molecular baraminology studies have not yet been performed on plant data. The chloroplast genomes of plant species may also be analyzed to calculate putative baramins with this new tool. This would add new types of baraminology studies to the ones that have been performed to date.




organelle, genome, baraminology, software




DigitalCommons@Cedarville provides a publication platform for fully open access journals, which means that all articles are available on the Internet to all users immediately upon publication. However, the opinions and sentiments expressed by the authors of articles published in our journals do not necessarily indicate the endorsement or reflect the views of DigitalCommons@Cedarville, the Centennial Library, or Cedarville University and its employees. The authors are solely responsible for the content of their work. Please address questions to dc@cedarville.edu.

Submission Type


Included in

Biology Commons



To view the content in your browser, please download Adobe Reader or, alternately,
you may Download the file to your hard drive.

NOTE: The latest versions of Adobe Reader do not support viewing PDF files within Firefox on Mac OS and if you are using a modern (Intel) Mac, there is no official plugin for viewing PDF files within the browser window.