Relevant bibliographies by topics / Statistics|Biology, Bioinformatics

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'Statistics|Biology, Bioinformatics'

Author: Grafiati
Published: 9 July 2021
Last updated: 29 July 2025

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Journal articles on the topic "Statistics|Biology, Bioinformatics"

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Rajpal, Deepak K. "Understanding Biology Through Bioinformatics." International Journal of Toxicology 24, no. 3 (2005): 147–52. http://dx.doi.org/10.1080/10915810590948325.

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During the journey from the discovery of DNA to be the source of genetic information and elucidation of double-helical nature of DNA molecule to the assembly of human genome sequence and there after, bioinformatics has become an integral part of modern biology. Bioinformatics relies substantially on significant contributions made by scientists in various fields, including but not limited to, linguistics, biology, mathematics, computer science, and statistics. There is an ever increasing amount of data to elucidate toxic mechanisms and/or adverse effects of xenobiotics in the field of toxicogen
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Sari, Indah Juwita, Eli Setiawati, Rihadatul Aisy, and Alpha Bayoh Jr. "Analysis of Teacher Readiness to Implement Bioinformatics to Biology Learning in Senior High School." Cybersecurity and Innovative Technology Journal 2, no. 2 (2024): 104–11. https://doi.org/10.53889/citj.v2i2.454.

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This study aimed to analyze teachers' readiness in applying bioinformatics to biology learning in senior high schools. Bioinformatics is a combination of computer science, statistics, and biology to analyze and interpret complex biological data. The application of bioinformatics into learning can foster students' realization of the real-life commitment of bioinformatics, enhance their understanding, and expand their curiosity about bioinformatics. The application of bioinformatics into biology learning needs to be supported by teacher readiness in terms of understanding, skills and factors tha
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Chen, Yi-Ping Phoebe, and Geoff McLachlan. "Bioinformatics Research in Australia." Asia-Pacific Biotech News 07, no. 03 (2003): 82–84. http://dx.doi.org/10.1142/s0219030303000211.

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Bioinformatics is the intersection of computer science, statistics, molecular biology and genetics. It is one of the most important emerging research areas of the 21st century and has already attracted worldwide interest. It is clear that major initiatives are being undertaken which will establish Australia both as a vital link in the international bioinformatics community for research and development and also as an Asia-Pacific service for bioinformatics. This article briefly notes some groups carrying out bioinformatics research in Australia.
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Perrière, Guy, and Jean Thioulouse. "On-line tools for sequence retrieval and multivariate statistics in molecular biology." Bioinformatics 12, no. 1 (1996): 63–69. http://dx.doi.org/10.1093/bioinformatics/12.1.63.

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Grover, Siddhant, Alexey Markin, Tavis K. Anderson, and Oliver Eulenstein. "Phylogenetic diversity statistics for all clades in a phylogeny." Bioinformatics 39, Supplement_1 (2023): i177—i184. http://dx.doi.org/10.1093/bioinformatics/btad263.

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Abstract The classic quantitative measure of phylogenetic diversity (PD) has been used to address problems in conservation biology, microbial ecology, and evolutionary biology. PD is the minimum total length of the branches in a phylogeny required to cover a specified set of taxa on the phylogeny. A general goal in the application of PD has been identifying a set of taxa of size k that maximize PD on a given phylogeny; this has been mirrored in active research to develop efficient algorithms for the problem. Other descriptive statistics, such as the minimum PD, average PD, and standard deviati
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Anuraga, Gangga, Fenny Fitriani, Rabiatul Adawiyah, Diva Aprilia Trisha Utami, and Laura Sekar Faramaysty. "Peningkatan Literasi Bioinformatika bagi Siswa Sekolah Menengah melalui Pelatihan Implementasi Sains Data." JAST : Jurnal Aplikasi Sains dan Teknologi 9, no. 1 (2025): 121–31. https://doi.org/10.33366/jast.v9i1.7081.

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Bioinformatics is an interdisciplinary field that integrates biology, statistics, and computer science to analyze large-scale biological data. In the context of secondary education, students' understanding of this concept is still minimal. This study aims to evaluate the effectiveness of a training on the Implementation of Data Science in Bioinformatics, organized by the Statistics Study Program at Universitas PGRI Adi Buana Surabaya as part of a community service activity. The training methodology used a hybrid approach combining offline and online sessions. Twelfth-grade science students fro
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Grisham, William, Natalie A. Schottler, Joanne Valli-Marill, Lisa Beck, and Jackson Beatty. "Teaching Bioinformatics and Neuroinformatics by Using Free Web-based Tools." CBE—Life Sciences Education 9, no. 2 (2010): 98–107. http://dx.doi.org/10.1187/cbe.09-11-0079.

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This completely computer-based module's purpose is to introduce students to bioinformatics resources. We present an easy-to-adopt module that weaves together several important bioinformatic tools so students can grasp how these tools are used in answering research questions. Students integrate information gathered from websites dealing with anatomy (Mouse Brain Library), quantitative trait locus analysis (WebQTL from GeneNetwork), bioinformatics and gene expression analyses (University of California, Santa Cruz Genome Browser, National Center for Biotechnology Information's Entrez Gene, and th
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Fogg, Christiana N. "ISMB 2016 offers outstanding science, networking, and celebration." F1000Research 5 (June 14, 2016): 1371. http://dx.doi.org/10.12688/f1000research.8640.1.

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The annual international conference on Intelligent Systems for Molecular Biology (ISMB) is the major meeting of the International Society for Computational Biology (ISCB). Over the past 23 years the ISMB conference has grown to become the world's largest bioinformatics/computational biology conference. ISMB 2016 will be the year's most important computational biology event globally. The conferences provide a multidisciplinary forum for disseminating the latest developments in bioinformatics/computational biology. ISMB brings together scientists from computer science, molecular biology, mathema
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Duan, Yibing. "Present Situation and Forecast of Bioinformatics in the Field of New Medicine Research and Development." E3S Web of Conferences 213 (2020): 03027. http://dx.doi.org/10.1051/e3sconf/202021303027.

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In the last several centuries, biology has accumulated a large number of data, which are disorganized and hard to be used repeatedly. Bioinformatics, synthesized informatics, statistics and some other subjects, makes them orderly and much more valuable. In drug discovery, Bioinformatics takes the place of some conventional ways because of low cast and high throughput. This article introduces the current situation and application of Bioinformatics in drug discovery and looks forward to the future, hoping to provide a Reference for the development of new drugs.
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Cindy Aulia Amanda, Khairunnisa Khairunnisa, Muhammad Fitra Affandi Hrp, et al. "Masa Depan Bio Informatika : Mengubah Data Menjadi Terapi." Jurnal Sistem Informasi dan Ilmu Komputer 3, no. 1 (2024): 17–23. https://doi.org/10.59581/jusiik-widyakarya.v3i1.4410.

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Bioinformatics is an interdisciplinary field that combines biology, computer science and statistics to analyze biological data and translate it into effective therapies. With technological advances, such as next-generation genetic sequencing, bioinformatics enables the development of personalized therapies based on an individual's genetic profile. This approach provides more effective treatment and reduces the risk of side effects. In addition, the integration of artificial intelligence (AI) accelerates big data analysis, predicts therapy response and identifies disease biomarkers. Despite cha
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Dissertations / Theses on the topic "Statistics|Biology, Bioinformatics"

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Franks, Alexander M. "Quantifying Sources of Variation in High-throughput Biology." Thesis, Harvard University, 2015. http://nrs.harvard.edu/urn-3:HUL.InstRepos:17463988.

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One of the central challenges in systems biology research is disentangling relevant and irrelevant sources of variation. While the relevant quantities are always context dependent, an important distinction can be drawn between variability due to biological processes and variability due measurement error. Biological variability includes variability between mRNA or protein abundances within a well defined condition, variability of these abundances across conditions (physiological variability), and between species or between subject variability. Technical variability includes measurement error
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Blocker, Alexander W. "Distributed and multiphase inference in theory and practice| Principles, modeling, and computation for high-throughput science." Thesis, Harvard University, 2013. http://pqdtopen.proquest.com/#viewpdf?dispub=3566820.

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<p> The rise of high-throughput scientific experimentation and data collection has introduced new classes of statistical and computational challenges. The technologies driving this data explosion are subject to complex new forms of measurement error, requiring sophisticated statistical approaches. Simultaneously, statistical computing must adapt to larger volumes of data and new computational environments, particularly parallel and distributed settings. This dissertation presents several computational and theoretical contributions to these challenges. </p><p> In chapter 1, we consider the p
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Wang, Qixin. "Genetic analysis of differentiation of T-helper lymphocytes." Thesis, University of Southern California, 2013. http://pqdtopen.proquest.com/#viewpdf?dispub=1546784.

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<p> In the human immune system, T-helper cells are able to differentiate into two lymphocyte subsets: Th1 and Th2. The intracellular signaling pathways of differentiation form a dynamic regulation network by secreting distinctive types of cytokines, while differentiation is regulated by two major gene loci: T-bet and GATA-3. We developed a system dynamics model to simulate the differentiation and re-differentiation process of T-helper cells, based on gene expression levels of T-bet and GATA-3 during differentiation of these cells. We arrived at three ultimate states of the model and came to th
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Sun, Guoli. "Significant distinct branches of hierarchical trees| A framework for statistical analysis and applications to biological data." Thesis, State University of New York at Stony Brook, 2015. http://pqdtopen.proquest.com/#viewpdf?dispub=3685086.

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<p> One of the most common goals of hierarchical clustering is finding those branches of a tree that form quantifiably distinct data subtypes. Achieving this goal in a statistically meaningful way requires (a) a measure of distinctness of a branch and (b) a test to determine the significance of the observed measure, applicable to all branches and across multiple scales of dissimilarity. </p><p> We formulate a method termed Tree Branches Evaluated Statistically for Tightness (TBEST) for identifying significantly distinct tree branches in hierarchical clusters. For each branch of the tree a me
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Li, Yang. "Statistical Methods for Large-Scale Integrative Genomics." Thesis, Harvard University, 2016. http://nrs.harvard.edu/urn-3:HUL.InstRepos:33493551.

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In the past 20 years, we have witnessed a significant advance of high-throughput genetic and genomic technologies. With the massively generated genomics data, there is a pressing need for statistical methods that can utilize them to make quantitative inference on substantive scientific questions. My research has been focusing on statistical methods for large-scale integrative genomics. The human genome encodes more than 20,000 genes, while the functions of about 50% (>10,000) genes remains unknown up to date. The determination of the functions of the poorly characterized genes is crucial for
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Zacharouli, Markella-Achilleia. "Characterization of immune infiltrate in early breast cancer based on a multiplex imaging method." Thesis, Uppsala universitet, Institutionen för biologisk grundutbildning, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-417716.

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Breast cancer is the most common type of cancer among women worldwide. Multiple studies have reported the role of tumor-immune interactions and mechanisms that the immune system uses to combat tumor cells. Therapies based on the immune response are evolving by time, but more research is required to understand and identify the patterns and relationships within the tumor microenvironment. This study aims to characterize immune cell expression patterns using a multiplex method and to investigate the way different subpopulations in breast cancer patients’ tissue samples are correlated with clinico
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Jung, Min Kyung. "Statistical methods for biological applications." [Bloomington, Ind.] : Indiana University, 2007. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:3278454.

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Thesis (Ph.D.)--Indiana University, Dept. of Mathematics, 2007.<br>Source: Dissertation Abstracts International, Volume: 68-10, Section: B, page: 6740. Adviser: Elizabeth A. Housworth. Title from dissertation home page (viewed May 20, 2008).
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Simonson, Matthew A. "Polygenic analysis of genome-wide SNP data." Thesis, University of Colorado at Boulder, 2013. http://pqdtopen.proquest.com/#viewpdf?dispub=3562047.

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<p> One of the central motivators behind genetic research is to understand how genetic variation relates to human health and disease. Recently, there has been a large-scale effort to find common genetic variants associated with many forms of disease and disorder using single nucleotide polymorphisms (SNPs). Several genome-wide association (GWAS) studies have successfully identified SNPs associated with phenotypes. However, the effect sizes attributed to individual variants is generally small, explaining only a very small amount of the genetic risk and heritability expected based on the estimat
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Wang, Zhi. "Module-Based Analysis for "Omics" Data." Thesis, North Carolina State University, 2015. http://pqdtopen.proquest.com/#viewpdf?dispub=3690212.

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<p> This thesis focuses on methodologies and applications of module-based analysis (MBA) in omics studies to investigate the relationships of phenotypes and biomarkers, e.g., SNPs, genes, and metabolites. As an alternative to traditional single&ndash;biomarker approaches, MBA may increase the detectability and reproducibility of results because biomarkers tend to have moderate individual effects but significant aggregate effect; it may improve the interpretability of findings and facilitate the construction of follow-up biological hypotheses because MBA assesses biomarker effects in a function
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Fernandez, Daniel. "Cell States and Cell Fate: Statistical and Computational Models in (Epi)Genomics." Thesis, Harvard University, 2015. http://nrs.harvard.edu/urn-3:HUL.InstRepos:14226043.

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This dissertation develops and applies several statistical and computational methods to the analysis of Next Generation Sequencing (NGS) data in order to gain a better understanding of our biology. In the rest of the chapter we introduce key concepts in molecular biology, and recent technological developments that help us better understand this complex science, which, in turn, provide the foundation and motivation for the subsequent chapters. In the second chapter we present the problem of estimating gene/isoform expression at the allelic level, and different models to solve this problem. Fir
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Books on the topic "Statistics|Biology, Bioinformatics"

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Zhou, Xiaobo. Computational systems bioinformatics: Methods and biomedical applications. World Scientific, 2008.

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1965-, Grant Gregory, ed. Statistical methods in bioinformatics: An introduction. Springer, 2001.

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Azuaje, Francisco. Bioinformatics and biomarker discovery: "omic" data analysis for personalised medicine. John Wiley & Sons, 2010.

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Azuaje, Francisco. Bioinformatics and biomarker discovery: "omic" data analysis for personalised medicine. John Wiley & Sons, 2010.

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Azuaje, Francisco. Bioinformatics and biomarker discovery: "omic" data analysis for personalised medicine. John Wiley & Sons, 2010.

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Vidyasagar, Mathukumalli. Computational Cancer Biology: An Interaction Network Approach. Springer London, 2012.

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1970-, Biswas Atanu, ed. Statistical advances in the biomedical sciences: Clinical trials, epidemiology, survival analysis, and bioinformatics. John Wiley & Sons, 2008.

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Igor, Akushevich, and Kravchenko Julia, eds. Cancer mortality and morbidity patterns in the U.S. population: An interdisciplinary approach. Springer, 2009.

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Zuckerman, Daniel M. Statistical physics of biomolecules: An introduction. CRC Press/Taylor & Francis, 2010.

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Priami, Corrado. Transactions on Computational Systems Biology XIV: Special Issue on Computational Models for Cell Processes. Springer Berlin Heidelberg, 2012.

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Book chapters on the topic "Statistics|Biology, Bioinformatics"

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Spouge, John L. "Sequence Alignment Statistics." In Problem Solving Handbook in Computational Biology and Bioinformatics. Springer US, 2010. http://dx.doi.org/10.1007/978-0-387-09760-2_3.

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Chaudhry, Afzal. "Bioinformatics." In Oxford Textbook of Medicine, edited by John D. Firth, Christopher P. Conlon, and Timothy M. Cox. Oxford University Press, 2020. http://dx.doi.org/10.1093/med/9780198746690.003.0011.

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Bioinformatics may be defined as ‘conceptualizing biology in terms of molecules and applying “informatics techniques” (e.g. applied mathematics, computer science and statistics) to understand and organize the information associated with these molecules, on a large scale’. Clinical bioinformatics may be defined as ‘the clinical application of bioinformatics-associated sciences and technologies to understand molecular mechanisms and potential therapies for human diseases’. If clinical bioinformatics is to deliver the integration of molecular and clinical data and thereby translate research knowl
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Tsunoda, Denise Fukumi, Heitor Silvério Lopes, and Ana Tereza Vasconcelos. "Web Tools for Molecular Biological Data Analysis." In Encyclopedia of Information Science and Technology, First Edition. IGI Global, 2005. http://dx.doi.org/10.4018/978-1-59140-553-5.ch546.

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Bioinformatics means solving problems arising from biology using methods from computer science. The National Center for Biotechnology Information (www.ncbi.nih.gov) defines bioinformatics as: “…the field of science in which biology, computer science, and information technology merge into a single discipline...There are three important sub-disciplines within bioinformatics: the development of new algorithms and statistics with which to access relationships among members of large data sets; the analysis and interpretation of various types of data including nucleotide and amino acid sequences, pr
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María Hernández-Domínguez, Edna, Laura Sofía Castillo-Ortega, Yarely García-Esquivel, Virginia Mandujano-González, Gerardo Díaz-Godínez, and Jorge Álvarez-Cervantes. "Bioinformatics as a Tool for the Structural and Evolutionary Analysis of Proteins." In Computational Biology and Chemistry. IntechOpen, 2020. http://dx.doi.org/10.5772/intechopen.89594.

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This chapter deals with the topic of bioinformatics, computational, mathematics, and statistics tools applied to biology, essential for the analysis and characterization of biological molecules, in particular proteins, which play an important role in all cellular and evolutionary processes of the organisms. In recent decades, with the next generation sequencing technologies and bioinformatics, it has facilitated the collection and analysis of a large amount of genomic, transcriptomic, proteomic, and metabolomic data from different organisms that have allowed predictions on the regulation of ex
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Thakur, Kushal, Dixit Sharma, Disha Chauhan, et al. "A Systems Biology Approach in Fisheries Science." In Systems Biology, Bioinformatics and Livestock Science. BENTHAM SCIENCE PUBLISHERS, 2023. http://dx.doi.org/10.2174/9789815165616123010009.

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Systems biology is concerned with complex interactions in biological systems, employing a holistic manner in addition to classical reductionism. Systems biology uses statistics, computational biology, and mathematical modelling to integrate and analyse vast data sets to obtain a better knowledge of biology and predict the behaviour of biological systems. It has gained attention in fisheries because of its ability to uncover novel processes. It can generate a panorama of events that occur within fish. In a systems biology approach, data from fish genomics, transcriptomics, proteomics, and metab
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Lu, Zhongyu, Qiang Xu, Murad Al-Rajab, and Lamogha Chiazor. "Importance of Information Working With Colon Cancer Research." In Research Anthology on Bioinformatics, Genomics, and Computational Biology. IGI Global, 2023. http://dx.doi.org/10.4018/979-8-3693-3026-5.ch041.

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Modern science helps us to understand the changing world around us, across fields such as biology, computer science, mathematics, statistics, chemistry, computational biology, biotechnology, biochemistry, and many others. An important branch of science that has had a large impact on the medical field is bioinformatics. This chapter introduces the importance of information science into colon cancer research. According to the American Cancer Association, in the United States in 2018, 97,220 new cases of colon cancer (CC) were identified. The research into this topic area is an immediate need to
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kiran, Goskula, Ankam shashank, G. Razia sultana begum, Ponaganti Shiva kishore, and Amitava mondal. "BIOINFORMATICS A RELIABLE TOOL IN AGRICULTURE." In Futuristic Trends in Biotechnology Volume 2 Book 26. Iterative International Publishers, Selfypage Developers Pvt Ltd, 2023. http://dx.doi.org/10.58532/v2bs26ch11.

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Bioinformatics is a multidisciplinary field of study that creates tools and software for analysing biological data. It aids in the evaluation and understanding of complex data in the numerous branches of biology and closely related sciences. It is possible to think of bioinformatics as a computer-based scientific discipline that combines computer science, biology, and mathematics to analyse and understand data from the fields of genomics and proteomics. The main components of bioinformatics are the collection and analysis of databases and the development of software tools and algorithms as a t
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Pathak, Upasana, Abhichandan Das, Pranjal Kumar Bora, and Sanchaita Rajkhowa. "Applications and Future Perspectives of Computational Approaches in Livestock Animals." In Systems Biology, Bioinformatics and Livestock Science. BENTHAM SCIENCE PUBLISHERS, 2023. http://dx.doi.org/10.2174/9789815165616123010018.

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Livestock is regarded as a critical point of access for enhanced food and nutrition. With the population explosion, an increase in the successful fulfillment of livestock production, including meat and dairy products, is necessary in the most ethical way. Fundamentally keeping the overall nutrition intact along with the health of both human and livestock animals is vital. Although there is an increment in production, it contributes to rising greenhouse gas (methane) emissions, thus damaging the environment. Inheriting novel technologies will not only help in the surplus upliftment of livestock
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Sharma, Yogesh Kumar, Sunayana Kundan Shivthare, Avinash Godharam Chaure, and Shital Vaibhav Ghotekar. "Advanced Learning and Bioinformatics in Innovative Drug Discovery Towards Bridging Biology." In Advances in Healthcare Information Systems and Administration. IGI Global, 2024. http://dx.doi.org/10.4018/979-8-3693-1874-4.ch002.

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Modern bioinformatics and artificial intelligence technologies are coming together to transform the process of developing pharmaceuticals, marking the beginning of an entirely novel phase in pharmaceutical discovery at the nexus of computational research and biological sciences. This work examines the relationship between statistics and biological processes, emphasizing the promise of significant change by combining artificial intelligence (AI) with bioinformatics methods to improve drug research. Incorporating computational methods, mathematical models, and machine learning procedures in comp
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Sagharchi, Seyyed Mohammad Amin Mousavi, Mohsen Sheykhhasan, Atousa Ghorbani, et al. "Genomics." In Advances in Bioinformatics and Biomedical Engineering. IGI Global, 2024. http://dx.doi.org/10.4018/979-8-3693-3192-7.ch002.

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Genomics is an exciting and rapidly evolving field at the intersection of biology, computer science, and statistics, which has made remarkable strides in recent years thanks to advancements in high-throughput sequencing technologies. This field allows us to analyze and understand the genetic code of organisms, from humans to microorganisms, shedding light on everything from the diagnosis and treatment of genetic disorders to the identification of disease-causing genes in pathogens, to the mysteries of biodiversity. With its wide range of applications, genomics is transforming our understanding
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Conference papers on the topic "Statistics|Biology, Bioinformatics"

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Piyaratne, Alisha, and Upeka Bandaranayake. "In silico Toxicity Analysis of Potential Wound Healing Drug Candidates to Assess Drug Suitability." In SLIIT INTERNATIONAL CONFERENCE ON ADVANCEMENTS IN SCIENCES AND HUMANITIES. Faculty of Humanities & Sciences, SLIIT, 2024. https://doi.org/10.54389/sseg9731.

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Drug development typically takes several years, but in-silico techniques, computational biology and chemical solutions can expedite toxicity analysis and other sections of the drug development process. Therefore, screening of potential drug candidates has become efficient. These techniques provide results quickly, cost-effectively, and without harming animals or humans. This research leverages bioinformatics to analyse the toxicity of chemical compounds in a potential wound-healing drug, specifically Bilirubin, Pinocembrin, and Resveratrol. Software such as Discovery Studios, Chem3D Pro, OpenB
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Wittkowski, Knut M., Asifa Haider, Ephraim Sehayek, et al. "Bioinformatics Tools Enabling U-Statistics for Microarrays." In Conference Proceedings. Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, 2006. http://dx.doi.org/10.1109/iembs.2006.260846.

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Wittkowski, Knut M., Asifa Haider, Ephraim Sehayek, et al. "Bioinformatics Tools Enabling U-Statistics for Microarrays." In Conference Proceedings. Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, 2006. http://dx.doi.org/10.1109/iembs.2006.4398192.

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"New framework for gene-based association analysis using GWAS summary statistics and functional annotations." In Bioinformatics of Genome Regulation and Structure/Systems Biology (BGRS/SB-2022) :. Institute of Cytology and Genetics, the Siberian Branch of the Russian Academy of Sciences, 2022. http://dx.doi.org/10.18699/sbb-2022-264.

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Ding, Yulian, Yi Pan, Ronald C. Geyer, Franco J. Vizeacoumar, Frederick S. Vizeacoumar, and Fang-Xiang Wu. "Deciphering Bladder Cancer-Related circRNA Biomarkers: An Ensemble Model Integrating Deep Learning and Statistics for circRNA Analysis." In BCB '24: 15th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics. ACM, 2024. https://doi.org/10.1145/3698587.3701465.

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Odenkirk, Melanie, David Reif, and Erin Baker. "An online structural-based connectivity and omic phenotype evaluations (SCOPE) cheminformatics toolbox for lipidomic data visualization." In 2022 AOCS Annual Meeting & Expo. American Oil Chemists' Society (AOCS), 2022. http://dx.doi.org/10.21748/nleu8917.

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Lipidomic analyses using mass spectrometry have traditionally been complicated by an abundance of isomeric species. The recent emergence of experimental platforms allowing for isomer separation has significantly benefitted lipidomic studies by allowing further speciation and the acquisition of species-specific information. Data interpretation for this detailed information, however, still faces challenges as existing lipid pathways are often defined such that single nodes represent entire lipid classes and not individual species (e.g., pathways may indicate that phosphatidylcholines as a class
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