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1st International Conference on Education, Science and Technology, ICON-EST 2018

作者： Siriwat, W. Muhardina, V. Thammarongtham, C. Kalapanulak, S. Saithong, T. Systems Biology and Bioinformatics Research Laboratory Pilot Plant Development and Training Institute King Mongkut's University of Technology Thonburi Bang Khun Thian Bangkok10150 Thailand Department of Agricultural Industrial Technology Faculty of Agricultural Technology University of SerambiMekkah Jl. TeungkuImumLueng Bata Batoh Banda Aceh Aceh23245 Indonesia Biochemical Engineering and Pilot Plant Research and Development Unit National Center for Genetic Engineering and Biotechnology King Mongkut's University of Technology Thonburi Bang KhunThian Bangkok10150 Thailand Bioinformatics and Systems Biology Program School of Bioresources and Technology King Mongkut's University of Technology Thonburi Bang KhunThian Bangkok10150 Thailand

The nitrogen assimilation pathway in cassava was reconstructed by comparative genomics approach to understand the underlying metabolism as well as the interaction between carbon and nitrogen assimilation towards the synthesis of metabolic phenotype. First, theproteins of cassava were annotated via sequence similarity search against genes of 11 template plants obtained from KEGG and PMN databases, employing reciprocal BLASTp(E-value ≤ 1x10-10, identity percentage ≥ 60, and coverage percentage ≥ 80). The template plants comprised well-known plant, starchy crops, nitrogen-fixing crops and crops that are evolutionarily related to cassava and includedArabidopsis thaliana, Oryzasativa, Zea mays, Ricinuscommunis, Solanumtuberosum, Brassica rapa, Cicerarietinum, Jatrophacurcas, Medicagotruncatula, Phaseolus vulgaris and Glycine *** pathway was then curatedwith reactions obtained from the CassavaCyc database to ensure full pathway *** was subsequently validated with cloned sequence of cassava from the GenBank and cassava transcriptome data from literature. The resulting N-assimilation pathway, covering the conversion of nitrate to amino acids (glutamine and glutamate),consists of 14 biochemical reactions corresponding to 59 genes, 73 proteins and 2 transport reactions. At least 92 percent of the identified proteins in the pathway were supported by the transcriptome data. In addition, the proposed N-assimilation pathway contains four additional enzymes, including glutamate synthase, nitrilase, formamidase and carbamoyl phosphate synthasecompared to the existing N-assimilation pathway in CassavaCyc database. Taken together, the N-assimilation pathway herein proposed identified reactions involved in N-assimilation and represents a forward step towards understanding metabolic basis for cassava yield as well as its phenotypic plasticity and adaptation to stress. © Published under licence by IOP Publishing Ltd.

关键词： Genes

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Single-nucleus analysis of accessible chromatin in developing mouse forebrain reveals cell-type-specific transcriptional regulation (vol 21, pg 432, 2018)

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NATURE NEUROSCIENCE 2018年第7期21卷 1015-1015页

作者： Preissl, Sebastian Fang, Rongxin Huang, Hui Zhao, Yuan Raviram, Ramya Gorkin, David U. Zhang, Yanxiao Sos, Brandon C. Afzal, Veena Dickel, Diane E. Kuan, Samantha Visel, Axel Pennacchio, Len A. Zhang, Kun Ren, Bing Ludwig Institute for Cancer Research La Jolla CA USA Center for Epigenomics Department of Cellular and Molecular Medicine University of California San Diego School of Medicine La Jolla CA USA Bioinformatics and Systems Biology Graduate Program University of California San Diego La Jolla CA USA Biomedical Sciences Graduate Program University of California San Diego La Jolla CA USA Department of Bioengineering University of California San Diego La Jolla CA USA Environmental Genomics and Systems Biology Division Lawrence Berkeley National Laboratory Berkeley CA USA US Department of Energy Joint Genome Institute Walnut Creek CA USA School of Natural Sciences University of California Merced Merced CA USA Comparative Biochemistry Program University of California Berkeley Berkeley CA USA Institute of Genomic Medicine Moores Cancer Center University of California San Diego School of Medicine La Jolla CA USA

Analysis of chromatin accessibility can reveal transcriptional regulatory sequences, but heterogeneity of primary tissues poses a significant challenge in mapping the precise chromatin landscape in specific cell types. Here we report single-nucleus ATAC-seq, a combinatorial barcoding-assisted single-cell assay for transposase-accessible chromatin that is optimized for use on flash-frozen primary tissue samples. We apply this technique to the mouse forebrain through eight developmental stages. Through analysis of more than 15,000 nuclei, we identify 20 distinct cell populations corresponding to major neuronal and non-neuronal cell types. We further define cell-type-specific transcriptional regulatory sequences, infer potential master transcriptional regulators and delineate developmental changes in forebrain cellular composition. Our results provide insight into the molecular and cellular dynamics that underlie forebrain development in the mouse and establish technical and analytical frameworks that are broadly applicable to other heterogeneous tissues.

关键词： Cell type diversity Chromatin Chromatin analysis Epigenomics

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A systems biology Approach to Identify Candidate Targets to Downregulate Angiogenic Gene Expression in Cancer

A Systems Biology Approach to Identify Candidate Targets to ...

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International Work Conference on Bio-inspired Intelligence (IWOBI)

作者： Calderon-Gomez Paola Man-Sai Aeón-Chan RA Mora-Rodriguez Master Program on Bioinformatics and Systems Biology University of Costa Rica (UCR) San José Costa Rica Faculty of Microbiology University of Costa Rica (UCR) San José Costa Rica

The control of angiogenesis in cancer has been recognized as a promising therapeutic target for many diseases like cancer. Specifically, the Angiopoietin-2 - Vascular Endothelial Growth Factor system has demonstrated special relevance in the regulation of angiogenesis, highlighting the importance of the complex coordination among vascular signaling molecules [3] for the identification of targets for future anti-angiogenic therapy. Current approaches to regulate the angiogenesis process focus their efforts only on VEGF regulation but this has proven ineffective in many kinds of cancer, prompting the need for further understanding of how the vasculature can be effectively targeted in tumors [9]. Given the complex properties of gene expression in this process, a systems biology approach is required to identify putative candidates to robustly regulate genes involved in angiogenesis. We propose a model with candidate targets to downregulate the angiogenic genes expression. We identified a strong regulation of the AKT1-ANGPT2-KDR axis by miR200B and miR200C. Also, we identified a strong regulation of SRC by miR34a. These candidate miRNAs could therefore have a potential for the development of novel therapeutic strategies against angiogenesis in cancer.

关键词： Biological system modeling Cancer Analytical models Data models Tumors systems biology Mathematical model

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miRNA networks regulating gene expression in response to tension or compression forces in the cells of the periodontal ligament

miRNA networks regulating gene expression in response to ten...

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BioInspired Processing (BIP), IEEE International Conference on

作者： Mariana Bonilla Valverde Rodrigo Mora Rodríguez Master Program on Bioinformatics and Systems Biology Postgraduate Program SEP University of Costa Rica 11501-2060 San José Costa Rica Faculty of Microbiology University of Costa Rica 11501-2060 San José Costa Rica

ISBN: (纸本)9781665470490

In response to force application, biological reactions occur in the periodontal ligament that causes the orthodontic tooth movement. Differential expression of genes such as ALPL, FGF7, PDRM1, and NR4A2 are involved in the exposure to tension or compression forces by contributing to bone remodeling. In this study, a systems biology approach is used in order to identify a modulator of gene expression when mechanical loadings are applied in periodontal ligament cells. We developed a mathematical model of the interaction network of ALPL and FGF7 with several miRNAs and the transcription factor modulators in BioNetUCR, Cytoscape and COPASI software. We found that miR129-2 has a negative control in ALPL, FGF7, NR4A2 and PRDM1 genes, while miRNA192 has a negative control in ALPL and FGF7 genes in compression and tension side. Both miRNAs are proposed for future experimental validation.

关键词： systems biology Loading Force Modulation Cells (biology) Bones Software

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Strategies for pathway-based analysis of genome-wide SNP data

Strategies for pathway-based analysis of genome-wide SNP dat...

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2011 Defense Science Research Conference and Expo, DSR 2011

作者： Patumcharoenpol, P. Chan, J. Prom-On, S. Meechai, A. Bioinformatics and Systems Biology Program King Mongkut's University of Technology Thonburi Bangkok Thailand School of Information Technology King Mongkut's University of Technology Thonburi Bangkok Thailand Computer Engineering Department King Mongkut's University of Technology Thonburi Bangkok Thailand Department of Chemical Engineering King Mongkut's University of Technology Thonburi Bangkok Thailand Biological Engineering Program King Mongkut's University of Technology Thonburi Bangkok Thailand

ISBN: (纸本)9781424492763

Numerous genome-wide association studies (GWAS) have been performed in order to determine the susceptible loci of diseases. However, most diseases still cannot be explained by a single locus. Pathway-based methods address this problem by combining those small effects into groups of related genes or pathways. However, because pathway-based approaches consist of multiple steps, there is much room for improvement. This paper presents an improved method for translating list of SNPs from GWAS into list of genes. We incrementally adjusted and compared different modifications applied to Parkinson's disease (PD) genome-wide SNP data and then used GSEA-P to analyze the resulting list of genes. After careful adjustments, we are able to identify more relevant pathways that were not found previously. © 2011 IEEE.

关键词： Genes

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Effects of Maternal and Lactational Exposure to 2-Hydroxy-4 Methoxybenzone on Development and Reproductive Organs in Male and Female Rat Offspring (vol 104, pg 35, 2015)

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BIRTH DEFECTS RESEARCH PART B-DEVELOPMENTAL AND REPRODUCTIVE TOXICOLOGY 2015年第3期104卷 140-140页

作者： Nakamura, Noriko Inselman, Amy L. White, Gene A. Chang, Ching-Wei Trbojevich, Raul A. Sephr, Estatira Voris, Kristie L. Patton, Ralph E. Bryant, Matthew S. Harrouk, Wafa McIntyre, Barry S. Foster, Paul M. D. Hansen, Deborah K. Division of Systems Biology National Center for Toxicological Research Food and Drug Administration Jefferson Arkansas Division of Bioinformatics and Biostatistics National Center for Toxicological Research Food and Drug Administration Jefferson Arkansas Division of Biochemical Toxicology National Center for Toxicological Research Food and Drug Administration Jefferson Arkansas Toxicologic Pathology Associates Jefferson Arkansas Center for Drug Evaluation and Research Food and Drug Administration Silver Spring Maryland National Toxicology Program National Institute of Environmental Health Sciences National Institutes of Health Research Triangle Park North Carolina

2-Hydroxy-4-methoxybenzophenone (HMB) is an ultraviolet (UV) absorbing compound used in many cosmetic products as a UV-protecting agent and in plastics for preventing UV-induced photodecomposition. HMB has been detected in over 95% of randomly collected human urine samples from adults and from premature infants, and it may have estrogenic *** determine the effects of maternal and lactational exposure to HMB on development and reproductive organs of offspring, time-mated female Harlan Sprague-Dawley rats were dosed with 0, 1000, 3000, 10,000, 25,000, or 50,000 ppm HMB (seven to eight per group) added to chow from gestation day 6 until weaning on postnatal day (PND) *** AND CONCLUSIONExposure to HMB was associated with reduced body and organ weights in female and male offspring. No significant differences were observed in the number of implantation sites/litter, mean resorptions/litter, % litters with resorptions, number and weights of live fetuses, or sex ratios between the control and HMB dose groups. Normalized anogenital distance in male pups at PND 23 was decreased in the highest dose group. Spermatocyte development was impaired in testes of male offspring in the highest dose group. In females, follicular development was delayed in the highest dose group. However, by evaluating levels of the compound in rat serum, the doses at which adverse events occurred are much higher than usual human exposure levels. Thus, exposure to less than 10,000 ppm HMB does not appear to be associated with adverse effects on the reproductive system in rats

关键词： 2-hydroxy-4-methoxybenzophenone body weight rats offspring testes ovary fetal exposure

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ASpli: Integrative analysis of splicing landscapes through RNA-Seq assays (Mar, btab141, 2021)

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bioinformatics 2021年第12期37卷 1783-1783页

作者： Mancini, Estefania Rabinovich, Andres Iserte, Javier Yanovsky, Marcelo Chernomoretz, Ariel Gene Regulation Stem Cells and Cancer Program Centre for Genomic Regulation (CRG) The Barcelona Institute of Science and Technology Barcelona Spain Integrative Systems Biology Fundacion Instituto Leloir Buenos Aires Argentina Instituto de Investigaciones Bioquímicas de Buenos Aires Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET) Buenos Aires Argentina DStructural Bioinformatics Fundacion Instituto Leloir Buenos Aires Argentina Comparative Genomics of Plant Development Fundacion Instituto Leloir Buenos Aires Argentina

Motivation Genome-wide analysis of alternative splicing has been a very active field of research since the early days of next generation sequencing technologies. Since then, ever-growing data availability and the development of increasingly sophisticated analysis methods have uncovered the complexity of the general splicing repertoire. A large number of splicing analysis methodologies exist, each of them presenting its own strengths and weaknesses. For instance, methods exclusively relying on junction information do not take advantage of the large majority of reads produced in an RNA-seq assay, isoform reconstruction methods might not detect novel intron retention events, some solutions can only handle canonical splicing events, and many existing methods can only perform pairwise *** In this contribution, we present ASpli, a computational suite implemented in R statistical language, that allows the identification of changes in both, annotated and novel alternative-splicing events and can deal with simple, multi-factor or paired experimental designs. Our integrative computational workflow, that considers the same GLM model applied to different sets of reads and junctions, allows computation of complementary splicing signals. Analyzing simulated and real data, we found that the consolidation of these signals resulted in a robust proxy of the occurrence of splicing alterations. While the analysis of junctions allowed us to uncover annotated as well as non-annotated events, read coverage signals notably increased recall capabilities at a very competitive performance when compared against other state-of-the-art splicing analysis *** and implementation ASpli is freely available from the Bioconductor project site https://***/doi:10.18129/*** information Supplementary data are available at bioinformatics online.

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Learning Cellular Objectives from Fluxes by Inverse Optimization

Learning Cellular Objectives from Fluxes by Inverse Optimiza...

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IEEE Annual Conference on Decision and Control

作者： Qi Zhao Arion Stettner Ed Reznik Daniel Segre Ioannis Ch. Paschalidis Dept. of Electrical and Computer Eng. and Division of Systems Engineering Boston University Department of Biomedical Engineering Boston University Bioinformatics Program Department of Biology and Department of Biomedical Engineering Boston University

ISBN: (纸本)9781479978878

Flux Balance Analysis (FBA) is a widely used approach for studying biochemical networks, and in particular the genome-scale metabolic network reconstructions. It formulates the problem of predicting a cell's chemical reaction fluxes as the linear optimization problem of maximizing a cellular objective (e.g., growth) subject to constraints capturing stoichiometry mass balances of the metabolic network and bounds that reflect the composition of the growth medium. In practice, however, reaction fluxes of the cells under specific growth conditions are available to be measured, but the primal FBA objective function is not necessarily known. Understanding its structure can elucidate the cellular metabolic control mechanisms and infer important information regarding an organism's evolution. To that end, we have developed an Inverse Flux Balance Analysis (InvFBA) method which is a novel inverse optimization-based framework for inferring metabolic objective functions. Within this framework, we present three different forms of objective functions: linear, quadratic, and non-parametric. We show that in all cases, the inverse problem is tractable and can be solved efficiently. We provide several numerical examples to show that the inference of the objective function is consistent with simulated flux data and actual measurements.

关键词： Linear programming Kernel Optimization Biochemistry Biomass Biomedical measurement

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Rewriting regulatory DNA to dissect and reprogram gene expression

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Cell 2025年

作者： Martyn, Gabriella E. Montgomery, Michael T. Jones, Hank Guo, Katherine Doughty, Benjamin R. Linder, Johannes Bisht, Deepa Xia, Fan Cai, Xiangmeng S. Chen, Ziwei Cochran, Kelly Lawrence, Kathryn A. Munson, Glen Pampari, Anusri Fulco, Charles P. Sahni, Nidhi Kelley, David R. Lander, Eric S. Kundaje, Anshul Engreitz, Jesse M. Department of Genetics Stanford University School of Medicine Stanford 94305 CA United States Basic Science and Engineering Initiative Stanford Children's Health Betty Irene Moore Children's Heart Center Stanford 94305 CA United States Calico Life Sciences LLC South San Francisco 94080 CA United States Department of Genitourinary Medical Oncology Division of Cancer Medicine The University of Texas MD Anderson Cancer Center Houston 77030 TX United States Department of Genomic Medicine The University of Texas MD Anderson Cancer Center Houston 77030 TX United States Department of Epigenetics and Molecular Carcinogenesis The University of Texas MD Anderson Cancer Center Houston 77230 TX United States Department of Bioengineering Stanford University Stanford 94305 CA United States Department of Computer Science Stanford University Stanford 94305 CA United States Novo Nordisk Foundation Center for Genomic Mechanisms of Disease Broad Institute of MIT and Harvard Cambridge 02142 MA United States Gene Regulation Observatory Broad Institute of MIT and Harvard Cambridge 02142 MA United States Broad Institute of MIT and Harvard Cambridge 02142 MA United States Department of Bioinformatics and Computational Biology The University of Texas MD Anderson Cancer Center Houston 77230 TX United States Quantitative and Computational Biosciences Program Baylor College of Medicine Houston 77030 TX United States Department of Biology MIT Cambridge 02139 MA United States Department of Systems Biology Harvard Medical School Boston 02115 MA United States Stanford Cardiovascular Institute Stanford University Stanford 94305 CA United States

Regulatory DNA provides a platform for transcription factor binding to encode cell-type-specific patterns of gene expression. However, the effects and programmability of regulatory DNA sequences remain difficult to map or predict. Here, we develop variant effects from flow-sorting experiments with CRISPR targeting screens (Variant-EFFECTS) to introduce hundreds of designed edits to endogenous regulatory DNA and quantify their effects on gene expression. We systematically dissect and reprogram 3 regulatory elements for 2 genes in 2 cell types. These data reveal endogenous binding sites with effects specific to genomic context, transcription factor motifs with cell-type-specific activities, and limitations of computational models for predicting the effect sizes of variants. We identify small edits that can tune gene expression over a large dynamic range, suggesting new possibilities for prime-editing-based therapeutics targeting regulatory DNA. Variant-EFFECTS provides a generalizable tool to dissect regulatory DNA and to identify genome editing reagents that tune gene expression in an endogenous context. © 2025 Elsevier Inc.

关键词： CRISPR enhancers gene regulation high-throughput screening non-coding variants predictive models prime editing RNA FlowFISH sequence design transcription factors

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SeqScreen: a biocuration platform for robust taxonomic and biological process characterization of nucleic acid sequences of interest

SeqScreen: a biocuration platform for robust taxonomic and b...

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IEEE International Conference on bioinformatics and Biomedicine

作者： Dreycey Albin Dan Nasko R. A. Leo Elworth Jacob Lu Advait Balaji Christian Diaz Nidhi Shah Jeremy Selengut Chris Hulme-Lowe Pravin Muthu Gene Godbold Mikael Lindvall Madeline Diep Adam Porter Mihai Pop Krista Ternus Todd J. Treangen Program in Systems Synthetic and Physical Biology Rice University Center for Bioinformatics and Computational Biology University of Maryland Department of Computer Science Rice University Signature Science LLC Fraunhofer Center for Experimental Software Engineering Department of Computer Science University of Maryland

ISBN: (纸本)9781728118680

Rapid advancements in synthetic biology and nucleic acid synthesis, in particular concerns about its intentional or accidental misuse, call for more sophisticated screening tools to identify genes of interest within short sequence fragments. One major gap in predicting genes of concern is the inadequacy of current tools and ontologies to describe the specific biological processes of pathogenic proteins. The objective of this work is to design software that sensitively assigns taxonomic classifications, functional annotations, and biological processes of interest to short nucleotide sequences of unknown origin (50bp-1,000bp). The overarching goal is to perform sensitive characterization of short sequences and highlight specific pathogenic biological processes of interest (BPoIs). The SeqScreen software executes these tasks in analytical workflows with Nextflow and outputs results in a tab-delimited report. Local and global alignments differentiate hits to taxonomically-related sequences from similar but unrelated sequences, and an ensemble approach leverages multiple tools and databases to assign a variety of functional terms to each query sequence. Final biological process assessments are made from the predicted functional annotations, which leverage information in pre-existing databases, as well as new custom biocurations. Machine learning models predict each biological process of interest on large protein databases before incorporation into the SeqScreen framework to streamline computational efficiency, ensure reproducible results, allow for version control, and facilitate the review of the automated predictions by expert biocurators. The SeqScreen source code is available at .

关键词： Biological Process interest Base Sequence Nucleic acids Version control protein database Database synthetic biology ANNOTATIONS Leverage

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