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Mark Boguski | |
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 Boguski in September 2013 |
Mark S. Boguski (died March 18, 2021) [1] [2] was an American pathologist specializing in computational analysis and structural biology. In 2001, he was elected to both the U.S. National Academy of Medicine and the American College of Medical Informatics. [3] [4]
In December 1986, Boguski earned his M.D. from the Washington University School of Medicine and his Ph.D. in molecular biology from the Division of Biology and Biomedical Sciences' Medical Scientist Training Program in St. Louis, Missouri. [5] [6] He was the first graduate student to be mentored by Jeffrey I. Gordon.
In 1989, Boguski became a Medical Staff Fellow under David J. Lipman at the National Institute of Diabetes and Digestive and Kidney Diseases at the United States' National Institutes of Health. He joined the National Center for Biotechnology Information as an investigator in 1990 and was tenured as a senior investigator in 1995.[ citation needed ]
Boguski served on the faculties of the National Institutes of Health, the Johns Hopkins University School of Medicine, Harvard Medical School, and as an executive in the biotechnology and pharmaceutical industries. He was a former vice president and global head of Genome and Protein Sciences at Novartis. In 2014, he became the chief medical officer of Liberty BioSecurity, LLC and founded the Precision Medicine Network.
He previously served as editor-in-chief of Genomics and has written a series of books titled Reimagining Cancer. [7]
Boguski's work in computational biology included algorithm development (e.g., Gibbs sampler, text mining), database design, development and implementation (dbEST, XREFdb, ArrayDB) and data mining, data analysis and data annotation. One database effort in particular, the database of Expressed Sequence Tags (dbEST, [8] 1993), has contributed to gene discovery and succeeding generations of genomics applications, namely transcript mapping, design and construction of microarrays, discovery in silico of single nucleotide polymorphisms and, ultimately, analysis and annotation of the human genome.
Bioinformatics is an interdisciplinary field of science that develops methods and software tools for understanding biological data, especially when the data sets are large and complex. Bioinformatics uses biology, chemistry, physics, computer science, computer programming, information engineering, mathematics and statistics to analyze and interpret biological data. The subsequent process of analyzing and interpreting data is referred to as computational biology.
Computational biology refers to the use of data analysis, mathematical modeling and computational simulations to understand biological systems and relationships. An intersection of computer science, biology, and big data, the field also has foundations in applied mathematics, chemistry, and genetics. It differs from biological computing, a subfield of computer science and engineering which uses bioengineering to build computers.
In genetics, an expressed sequence tag (EST) is a short sub-sequence of a cDNA sequence. ESTs may be used to identify gene transcripts, and were instrumental in gene discovery and in gene-sequence determination. The identification of ESTs has proceeded rapidly, with approximately 74.2 million ESTs now available in public databases. EST approaches have largely been superseded by whole genome and transcriptome sequencing and metagenome sequencing.
Computational genomics refers to the use of computational and statistical analysis to decipher biology from genome sequences and related data, including both DNA and RNA sequence as well as other "post-genomic" data. These, in combination with computational and statistical approaches to understanding the function of the genes and statistical association analysis, this field is also often referred to as Computational and Statistical Genetics/genomics. As such, computational genomics may be regarded as a subset of bioinformatics and computational biology, but with a focus on using whole genomes to understand the principles of how the DNA of a species controls its biology at the molecular level and beyond. With the current abundance of massive biological datasets, computational studies have become one of the most important means to biological discovery.
The completion of the human genome sequencing in the early 2000s was a turning point in genomics research. Scientists have conducted series of research into the activities of genes and the genome as a whole. The human genome contains around 3 billion base pairs nucleotide, and the huge quantity of data created necessitates the development of an accessible tool to explore and interpret this information in order to investigate the genetic basis of disease, evolution, and biological processes. The field of genomics has continued to grow, with new sequencing technologies and computational tool making it easier to study the genome.
The Reference Sequence (RefSeq) database is an open access, annotated and curated collection of publicly available nucleotide sequences and their protein products. RefSeq was introduced in 2000. This database is built by National Center for Biotechnology Information (NCBI), and, unlike GenBank, provides only a single record for each natural biological molecule for major organisms ranging from viruses to bacteria to eukaryotes.
TSR3, or TSR3 Ribosome Maturation Factor, is a hypothetical human protein found on chromosome 16. Its protein is 312 amino acids long and its cDNA has 1214 base pairs. It was previously designated C16orf42.
Immunomics is the study of immune system regulation and response to pathogens using genome-wide approaches. With the rise of genomic and proteomic technologies, scientists have been able to visualize biological networks and infer interrelationships between genes and/or proteins; recently, these technologies have been used to help better understand how the immune system functions and how it is regulated. Two thirds of the genome is active in one or more immune cell types and less than 1% of genes are uniquely expressed in a given type of cell. Therefore, it is critical that the expression patterns of these immune cell types be deciphered in the context of a network, and not as an individual, so that their roles be correctly characterized and related to one another. Defects of the immune system such as autoimmune diseases, immunodeficiency, and malignancies can benefit from genomic insights on pathological processes. For example, analyzing the systematic variation of gene expression can relate these patterns with specific diseases and gene networks important for immune functions.
METTL26, previously designated C16orf13, is a protein-coding gene for Methyltransferase Like 26, also known as JFP2. Though the function of this gene is unknown, various data have revealed that it is expressed at high levels in various cancerous tissues. Underexpression of this gene has also been linked to disease consequences in humans.
LOC105377021 is a protein which in humans is encoded by the LOC105377021 gene. LOC105377021 exhibits expressional pathology related to breast cancer, specifically triple negative breast cancer. LOC105377021 contains a serine rich region in addition to predicted alpha helix motifs.
Leucine rich repeat containing 24 is a protein that, in humans, is encoded by the LRRC24 gene. The protein is represented by the official symbol LRRC24, and is alternatively known as LRRC14OS. The function of LRRC24 is currently unknown. It is a member of the leucine-rich repeat (LRR) superfamily of proteins.
Uncharacterized protein Chromosome 16 Open Reading Frame 71 is a protein in humans, encoded by the C16orf71 gene. The gene is expressed in epithelial tissue of the respiratory system, adipose tissue, and the testes. Predicted associated biological processes of the gene include regulation of the cell cycle, cell proliferation, apoptosis, and cell differentiation in those tissue types. 1357 bp of the gene are antisense to spliced genes ZNF500 and ANKS3, indicating the possibility of regulated alternate expression.
Uncharacterized protein C12orf60 is a protein that in humans is encoded by the C12orf60 gene. The gene is also known as LOC144608 or MGC47869. The protein lacks transmembrane domains and helices, but it is rich in alpha-helices. It is predicted to localize in the nucleus.
Proline-rich protein 30 is a protein in humans that is encoded for by the PRR30 gene. PRR30 is a member in the family of Proline-rich proteins characterized by their intrinsic lack of structure. Copy number variations in the PRR30 gene have been associated with an increased risk for neurofibromatosis.
Transcriptomics technologies are the techniques used to study an organism's transcriptome, the sum of all of its RNA transcripts. The information content of an organism is recorded in the DNA of its genome and expressed through transcription. Here, mRNA serves as a transient intermediary molecule in the information network, whilst non-coding RNAs perform additional diverse functions. A transcriptome captures a snapshot in time of the total transcripts present in a cell. Transcriptomics technologies provide a broad account of which cellular processes are active and which are dormant. A major challenge in molecular biology is to understand how a single genome gives rise to a variety of cells. Another is how gene expression is regulated.
FAM71E1, also known as Family With Sequence Similarity 71 Member E1, is a protein that in humans is encoded by the FAM71E1 gene. It is thought to be ubiquitously expressed at low levels throughout the body, and it is conserved in vertebrates, particularly mammals and some reptiles. The protein is localized to the nucleus and can be exported to the cytoplasm.
C7orf50 is a gene in humans that encodes a protein known as C7orf50. This gene is ubiquitously expressed in the kidneys, brain, fat, prostate, spleen, among 22 other tissues and demonstrates low tissue specificity. C7orf50 is conserved in chimpanzees, Rhesus monkeys, dogs, cows, mice, rats, and chickens, along with 307 other organisms from mammals to fungi. This protein is predicted to be involved with the import of ribosomal proteins into the nucleus to be assembled into ribosomal subunits as a part of rRNA processing. Additionally, this gene is predicted to be a microRNA (miRNA) protein coding host gene, meaning that it may contain miRNA genes in its introns and/or exons.
Chromosome 1 Opening Reading Frame 94 or C1orf94 is a protein in human coded by the C1orf94 gene. The function of this protein is still poorly understood.
C13orf42 is a protein which, in humans, is encoded by the gene chromosome 13 open reading frame 42 (C13orf42). RNA sequencing data shows low expression of the C13orf42 gene in a variety of tissues. The C13orf42 protein is predicted to be localized in the mitochondria, nucleus, and cytosol. Tertiary structure predictions for C13orf42 indicate multiple alpha helices.
Chromosome 12 open reading frame 71 (c12orf71) is a protein which in humans is encoded by c12orf71 gene. The protein is also known by the alias LOC728858.
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