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Computational Biology Commons

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Full-Text Articles in Computational Biology

From Fair To Cure: Guidelines For Computational Models Of Biological Systems, Herbert M. Sauro, Eran Agmon, Michael L. Blinov, John H. Gennari, Joseph L. Hellerstein, Adel Heydarabadipour, Bartholomew E. Jardine, Elebeoba May, David P. Nickerson, Lucian P. Smith, Gary D. Bader, Frank T. Bergmann, Patrick M. Boyle, Andreas Dräger, James R. Faeder, Song Feng, Juliana Freire, Fabian Fröhlich, James A. Glazier, Thomas E. Gorochowski, Tomas Helikar, Henning Hermjakob, Stefan Hoops, Peter Hunter, Princess I. Imoukhuede, Sarah M. Keating, Matthias König, Reinhard Laubenbacher, Leslie M. Loew, Carlos F. Lopez, William W. Lytton, Rahuman S. Malik-Sheriff, Andrew Mcculloch, Pedro Mendes, Lealem Mulugeta, Chris J. Myers, Jerry G. Myers, Anna Niarakis, David D. Van Niekerk, Brett G. Olivier, Alexander A. Patrie, Ellen M. Quardokus, Nicole Radde, Johann M. Rohwer, Sven Sahle, James C. Schaff, Falk Schreiber, T. J. Sego, Janis Shin, Jacky L. Snoep, Rajanikanth Vadigepalli, H. Steven Wiley, Dagmar Waltemath, Ion I. Moraru Mar 2026

From Fair To Cure: Guidelines For Computational Models Of Biological Systems, Herbert M. Sauro, Eran Agmon, Michael L. Blinov, John H. Gennari, Joseph L. Hellerstein, Adel Heydarabadipour, Bartholomew E. Jardine, Elebeoba May, David P. Nickerson, Lucian P. Smith, Gary D. Bader, Frank T. Bergmann, Patrick M. Boyle, Andreas Dräger, James R. Faeder, Song Feng, Juliana Freire, Fabian Fröhlich, James A. Glazier, Thomas E. Gorochowski, Tomas Helikar, Henning Hermjakob, Stefan Hoops, Peter Hunter, Princess I. Imoukhuede, Sarah M. Keating, Matthias König, Reinhard Laubenbacher, Leslie M. Loew, Carlos F. Lopez, William W. Lytton, Rahuman S. Malik-Sheriff, Andrew Mcculloch, Pedro Mendes, Lealem Mulugeta, Chris J. Myers, Jerry G. Myers, Anna Niarakis, David D. Van Niekerk, Brett G. Olivier, Alexander A. Patrie, Ellen M. Quardokus, Nicole Radde, Johann M. Rohwer, Sven Sahle, James C. Schaff, Falk Schreiber, T. J. Sego, Janis Shin, Jacky L. Snoep, Rajanikanth Vadigepalli, H. Steven Wiley, Dagmar Waltemath, Ion I. Moraru

Computational Medicine Center Faculty Papers

Guidelines for managing scientific data have been established under the FAIR principles, requiring that data be Findable, Accessible, Interoperable, and Reusable. In many scientific disciplines, especially computational biology, both data and models are key to progress. For this reason, and recognizing that such models are a very special type of "data", we argue that computational models, especially mechanistic models prevalent in medicine, physiology and systems biology, deserve a complementary set of guidelines. We propose the CURE principles, emphasizing that models should be Credible, Understandable, Reproducible, and Extensible. We delve into each principle, discussing verification, validation, and uncertainty quantification for model …


A Tissue Renewal-Based Mechanism Drives Colon Tumorigenesis, Ryan M. Boman, Gilberto Schleiniger, Christopher Raymond, Juan P. Palazzo, Anne Shehab, Bruce M. Boman Dec 2025

A Tissue Renewal-Based Mechanism Drives Colon Tumorigenesis, Ryan M. Boman, Gilberto Schleiniger, Christopher Raymond, Juan P. Palazzo, Anne Shehab, Bruce M. Boman

Department of Pathology, Anatomy, and Cell Biology Faculty Papers

Our Goal is to identify how colorectal cancer (CRC) arises in the single-layered cell epithelium (simple columnar epithelium) that lines the luminal surface of the large intestine. Background: We recently reported that the dynamic organization of cells in colonic epithelium is encoded by five biological rules and conjectured that colon tumorigenesis involves an autocatalytic tissue renewal reaction. Introduction Our objective was to define how altered crypt turnover explains tissue disorganization that leads to adenoma morphogenesis and CRC. Hypothesis: Changes in rate of tissue renewal-based cell polymerization leads to epithelial expansion and tissue disorganization during adenoma histogenesis. Methods: Accordingly, we created …


From Sampling To Simulating: Single-Cell Multiomics In Systems Pathophysiological Modeling, Alexandra Manchel, Michelle M. Gee, Rajanikanth Vadigepalli Dec 2024

From Sampling To Simulating: Single-Cell Multiomics In Systems Pathophysiological Modeling, Alexandra Manchel, Michelle M. Gee, Rajanikanth Vadigepalli

Department of Pathology, Anatomy, and Cell Biology Faculty Papers

As single-cell omics data sampling and acquisition methods have accumulated at an unprecedented rate, various data analysis pipelines have been developed for the inference of cell types, cell states and their distribution, state transitions, state trajectories, and state interactions. This presents a new opportunity in which single-cell omics data can be utilized to generate high-resolution, high-fidelity computational models. In this review, we discuss how single-cell omics data can be used to build computational models to simulate biological systems at various scales. We propose that single-cell data can be integrated with physiological information to generate organ-specific models, which can then be …


Understanding Potassium Toxicity Stress Responses Of The Extremophyte Schrenkiella Parvula Using Systems Biology Approaches, Pramod Pantha Jul 2021

Understanding Potassium Toxicity Stress Responses Of The Extremophyte Schrenkiella Parvula Using Systems Biology Approaches, Pramod Pantha

LSU Doctoral Dissertations

Schrenkiella parvula is an extremophyte model closely related to Arabidopsis thaliana and Brassica crops. Its natural habitat includes shores of saline lakes in the Irano-Turanian region. It has adapted to grow in soils rich in multiple salts including Na+ and K+. I have investigated the genetic basis for high K+ tolerance in plants using S. parvula as a stress tolerant model compared to the premier plant model, Arabidopsis thaliana which is highly sensitive to salt stresses using physiological, ionomic, transcriptomic, and metabolomic approaches. Under high K+ stress, root system architecture changes significantly compared to control …


Biases And Blind-Spots In Genome-Wide Crispr-Cas9 Knockout Screens, Merve Dede May 2021

Biases And Blind-Spots In Genome-Wide Crispr-Cas9 Knockout Screens, Merve Dede

Dissertations and Theses (Open Access)

Adaptation of the bacterial CRISPR-Cas9 system to mammalian cells revolutionized the field of functional genomics, enabling genome-scale genetic perturbations to study essential genes, whose loss of function results in a severe fitness defect. There are two types of essential genes in a cell. Core essential genes are absolutely required for growth and proliferation in every cell type. On the other hand, context-dependent essential genes become essential in an environmental or genetic context. The concept of context-dependent gene essentiality is particularly important in cancer, since killing cancer cells selectively without harming surrounding healthy tissue remains a major challenge. The toxicity of …


Pathway-Extended Gene Expression Signatures Integrate Novel Biomarkers That Improve Predictions Of Patient Responses To Kinase Inhibitors, Ashis Jem Bagchee-Clark, Eliseos J. Mucaki, Tyson Whitehead, Peter Rogan Nov 2020

Pathway-Extended Gene Expression Signatures Integrate Novel Biomarkers That Improve Predictions Of Patient Responses To Kinase Inhibitors, Ashis Jem Bagchee-Clark, Eliseos J. Mucaki, Tyson Whitehead, Peter Rogan

Biochemistry Publications

No abstract provided.


Metabolic Network Analysis Of Filamentous Cyanobacteria, Daniel Alexis Norena-Caro Jun 2020

Metabolic Network Analysis Of Filamentous Cyanobacteria, Daniel Alexis Norena-Caro

LSU Doctoral Dissertations

Cyanobacteria were the first organisms to use oxygenic photosynthesis, converting CO2 into useful organic chemicals. However, the chemical industry has historically relied on fossil raw materials to produce organic precursors, which has contributed to global warming. Thus, cyanobacteria have emerged as sustainable stakeholders for biotechnological production. The filamentous cyanobacterium Anabaena sp. UTEX 2576 can metabolize multiple sources of Nitrogen and was studied as a platform for biotechnological production of high-value chemicals (i.e., pigments, antioxidants, vitamins and secondary metabolites). From a Chemical engineering perspective, the biomass generation in this organism was thoroughly studied by interpreting the cell as a microbial …


Understanding Huntington's Disease Using Machine Learning Approaches, Sonali Lokhande Dec 2017

Understanding Huntington's Disease Using Machine Learning Approaches, Sonali Lokhande

KGI Theses and Dissertations

Huntington’s disease (HD) is a debilitating neurodegenerative disorder with a complex pathophysiology. Despite extensive studies to study the disease, the sequence of events through which mutant Huntingtin (mHtt) protein executes its action still remains elusive. The phenotype of HD is an outcome of numerous processes initiated by the mHtt protein along with other proteins that act as either suppressors or enhancers of the effects of mHtt protein and PolyQ aggregates. Utilizing an integrative systems biology approach, I construct and analyze a Huntington’s disease integrome using human orthologs of protein interactors of wild type and mHtt protein. Analysis of this integrome …


Phenotypic Robustness And The Assortativity Signature Of Human Transcription Factor Networks, Dov A. Pechenick, Joshua L. Payne, Jason H. Moore Aug 2014

Phenotypic Robustness And The Assortativity Signature Of Human Transcription Factor Networks, Dov A. Pechenick, Joshua L. Payne, Jason H. Moore

Dartmouth Scholarship

Many developmental, physiological, and behavioral processes depend on the precise expression of genes in space and time. Such spatiotemporal gene expression phenotypes arise from the binding of sequence-specific transcription factors (TFs) to DNA, and from the regulation of nearby genes that such binding causes. These nearby genes may themselves encode TFs, giving rise to a transcription factor network (TFN), wherein nodes represent TFs and directed edges denote regulatory interactions between TFs. Computational studies have linked several topological properties of TFNs - such as their degree distribution - with the robustness of a TFN's gene expression phenotype to genetic and environmental …


Systems Biology Approaches To Probe Gene Regulation In Bacteria, Diogo F. Troggian Veiga Aug 2012

Systems Biology Approaches To Probe Gene Regulation In Bacteria, Diogo F. Troggian Veiga

Dissertations and Theses (Open Access)

Mechanisms that allow pathogens to colonize the host are not the product of isolated genes, but instead emerge from the concerted operation of regulatory networks. Therefore, identifying components and the systemic behavior of networks is necessary to a better understanding of gene regulation and pathogenesis. To this end, I have developed systems biology approaches to study transcriptional and post-transcriptional gene regulation in bacteria, with an emphasis in the human pathogen Mycobacterium tuberculosis (Mtb).

First, I developed a network response method to identify parts of the Mtb global transcriptional regulatory network utilized by the pathogen to counteract phagosomal stresses …