Comparing Bioinformatics Software Development by Computer Scientists and Biologists: an Exploratory Study
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Programming Paradigms & Object-Oriented
4.3 (Programming Paradigms & Object-Oriented- Computer Science 9608 Programming) with Majid Tahir Syllabus Content: 4.3.1 Programming paradigms Show understanding of what is meant by a programming paradigm Show understanding of the characteristics of a number of programming paradigms (low- level, imperative (procedural), object-oriented, declarative) – low-level programming Demonstrate an ability to write low-level code that uses various address modes: o immediate, direct, indirect, indexed and relative (see Section 1.4.3 and Section 3.6.2) o imperative programming- see details in Section 2.3 (procedural programming) Object-oriented programming (OOP) o demonstrate an ability to solve a problem by designing appropriate classes o demonstrate an ability to write code that demonstrates the use of classes, inheritance, polymorphism and containment (aggregation) declarative programming o demonstrate an ability to solve a problem by writing appropriate facts and rules based on supplied information o demonstrate an ability to write code that can satisfy a goal using facts and rules Programming paradigms 1 4.3 (Programming Paradigms & Object-Oriented- Computer Science 9608 Programming) with Majid Tahir Programming paradigm: A programming paradigm is a set of programming concepts and is a fundamental style of programming. Each paradigm will support a different way of thinking and problem solving. Paradigms are supported by programming language features. Some programming languages support more than one paradigm. There are many different paradigms, not all mutually exclusive. Here are just a few different paradigms. Low-level programming paradigm The features of Low-level programming languages give us the ability to manipulate the contents of memory addresses and registers directly and exploit the architecture of a given processor. -
Bioconductor: Open Software Development for Computational Biology and Bioinformatics Robert C
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Collection Of Biostatistics Research Archive Bioconductor Project Bioconductor Project Working Papers Year 2004 Paper 1 Bioconductor: Open software development for computational biology and bioinformatics Robert C. Gentleman, Department of Biostatistical Sciences, Dana Farber Can- cer Institute Vincent J. Carey, Channing Laboratory, Brigham and Women’s Hospital Douglas J. Bates, Department of Statistics, University of Wisconsin, Madison Benjamin M. Bolstad, Division of Biostatistics, University of California, Berkeley Marcel Dettling, Seminar for Statistics, ETH, Zurich, CH Sandrine Dudoit, Division of Biostatistics, University of California, Berkeley Byron Ellis, Department of Statistics, Harvard University Laurent Gautier, Center for Biological Sequence Analysis, Technical University of Denmark, DK Yongchao Ge, Department of Biomathematical Sciences, Mount Sinai School of Medicine Jeff Gentry, Department of Biostatistical Sciences, Dana Farber Cancer Institute Kurt Hornik, Computational Statistics Group, Department of Statistics and Math- ematics, Wirtschaftsuniversitat¨ Wien, AT Torsten Hothorn, Institut fuer Medizininformatik, Biometrie und Epidemiologie, Friedrich-Alexander-Universitat Erlangen-Nurnberg, DE Wolfgang Huber, Department for Molecular Genome Analysis (B050), German Cancer Research Center, Heidelberg, DE Stefano Iacus, Department of Economics, University of Milan, IT Rafael Irizarry, Department of Biostatistics, Johns Hopkins University Friedrich Leisch, Institut fur¨ Statistik und Wahrscheinlichkeitstheorie, Technische Universitat¨ Wien, AT Cheng Li, Department of Biostatistical Sciences, Dana Farber Cancer Institute Martin Maechler, Seminar for Statistics, ETH, Zurich, CH Anthony J. Rossini, Department of Medical Education and Biomedical Informat- ics, University of Washington Guenther Sawitzki, Statistisches Labor, Institut fuer Angewandte Mathematik, DE Colin Smith, Department of Molecular Biology, The Scripps Research Institute, San Diego Gordon K. -
Bioinformatics 1
Bioinformatics 1 Bioinformatics School School of Science, Engineering and Technology (http://www.stmarytx.edu/set/) School Dean Ian P. Martines, Ph.D. ([email protected]) Department Biological Science (https://www.stmarytx.edu/academics/set/undergraduate/biological-sciences/) Bioinformatics is an interdisciplinary and growing field in science for solving biological, biomedical and biochemical problems with the help of computer science, mathematics and information technology. Bioinformaticians are in high demand not only in research, but also in academia because few people have the education and skills to fill available positions. The Bioinformatics program at St. Mary’s University prepares students for graduate school, medical school or entry into the field. Bioinformatics is highly applicable to all branches of life sciences and also to fields like personalized medicine and pharmacogenomics — the study of how genes affect a person’s response to drugs. The Bachelor of Science in Bioinformatics offers three tracks that students can choose. • Bachelor of Science in Bioinformatics with a minor in Biology: 120 credit hours • Bachelor of Science in Bioinformatics with a minor in Computer Science: 120 credit hours • Bachelor of Science in Bioinformatics with a minor in Applied Mathematics: 120 credit hours Students will take 23 credit hours of core Bioinformatics classes, which included three credit hours of internship or research and three credit hours of a Bioinformatics Capstone course. BS Bioinformatics Tracks • Bachelor of Science -
13 Genomics and Bioinformatics
Enderle / Introduction to Biomedical Engineering 2nd ed. Final Proof 5.2.2005 11:58am page 799 13 GENOMICS AND BIOINFORMATICS Spencer Muse, PhD Chapter Contents 13.1 Introduction 13.1.1 The Central Dogma: DNA to RNA to Protein 13.2 Core Laboratory Technologies 13.2.1 Gene Sequencing 13.2.2 Whole Genome Sequencing 13.2.3 Gene Expression 13.2.4 Polymorphisms 13.3 Core Bioinformatics Technologies 13.3.1 Genomics Databases 13.3.2 Sequence Alignment 13.3.3 Database Searching 13.3.4 Hidden Markov Models 13.3.5 Gene Prediction 13.3.6 Functional Annotation 13.3.7 Identifying Differentially Expressed Genes 13.3.8 Clustering Genes with Shared Expression Patterns 13.4 Conclusion Exercises Suggested Reading At the conclusion of this chapter, the reader will be able to: & Discuss the basic principles of molecular biology regarding genome science. & Describe the major types of data involved in genome projects, including technologies for collecting them. 799 Enderle / Introduction to Biomedical Engineering 2nd ed. Final Proof 5.2.2005 11:58am page 800 800 CHAPTER 13 GENOMICS AND BIOINFORMATICS & Describe practical applications and uses of genomic data. & Understand the major topics in the field of bioinformatics and DNA sequence analysis. & Use key bioinformatics databases and web resources. 13.1 INTRODUCTION In April 2003, sequencing of all three billion nucleotides in the human genome was declared complete. This landmark of modern science brought with it high hopes for the understanding and treatment of human genetic disorders. There is plenty of evidence to suggest that the hopes will become reality—1631 human genetic diseases are now associated with known DNA sequences, compared to the less than 100 that were known at the initiation of the Human Genome Project (HGP) in 1990. -
Paradigms of Computer Programming
Paradigms of computer programming l This course aims to teach programming as a unified discipline that covers all programming languages l We cover the essential concepts and techniques in a uniform framework l Second-year university level: requires some programming experience and mathematics (sets, lists, functions) l The course covers four important themes: l Programming paradigms l Mathematical semantics of programming l Data abstraction l Concurrency l Let’s see how this works in practice Hundreds of programming languages are in use... So many, how can we understand them all? l Key insight: languages are based on paradigms, and there are many fewer paradigms than languages l We can understand many languages by learning few paradigms! What is a paradigm? l A programming paradigm is an approach to programming a computer based on a coherent set of principles or a mathematical theory l A program is written to solve problems l Any realistic program needs to solve different kinds of problems l Each kind of problem needs its own paradigm l So we need multiple paradigms and we need to combine them in the same program How can we study multiple paradigms? l How can we study multiple paradigms without studying multiple languages (since most languages only support one, or sometimes two paradigms)? l Each language has its own syntax, its own semantics, its own system, and its own quirks l We could pick three languages, like Java, Erlang, and Haskell, and structure our course around them l This would make the course complicated for no good reason -
The Machine That Builds Itself: How the Strengths of Lisp Family
Khomtchouk et al. OPINION NOTE The Machine that Builds Itself: How the Strengths of Lisp Family Languages Facilitate Building Complex and Flexible Bioinformatic Models Bohdan B. Khomtchouk1*, Edmund Weitz2 and Claes Wahlestedt1 *Correspondence: [email protected] Abstract 1Center for Therapeutic Innovation and Department of We address the need for expanding the presence of the Lisp family of Psychiatry and Behavioral programming languages in bioinformatics and computational biology research. Sciences, University of Miami Languages of this family, like Common Lisp, Scheme, or Clojure, facilitate the Miller School of Medicine, 1120 NW 14th ST, Miami, FL, USA creation of powerful and flexible software models that are required for complex 33136 and rapidly evolving domains like biology. We will point out several important key Full list of author information is features that distinguish languages of the Lisp family from other programming available at the end of the article languages and we will explain how these features can aid researchers in becoming more productive and creating better code. We will also show how these features make these languages ideal tools for artificial intelligence and machine learning applications. We will specifically stress the advantages of domain-specific languages (DSL): languages which are specialized to a particular area and thus not only facilitate easier research problem formulation, but also aid in the establishment of standards and best programming practices as applied to the specific research field at hand. DSLs are particularly easy to build in Common Lisp, the most comprehensive Lisp dialect, which is commonly referred to as the “programmable programming language.” We are convinced that Lisp grants programmers unprecedented power to build increasingly sophisticated artificial intelligence systems that may ultimately transform machine learning and AI research in bioinformatics and computational biology. -
Use of Bioinformatics Resources and Tools by Users of Bioinformatics Centers in India Meera Yadav University of Delhi, [email protected]
University of Nebraska - Lincoln DigitalCommons@University of Nebraska - Lincoln Library Philosophy and Practice (e-journal) Libraries at University of Nebraska-Lincoln 2015 Use of Bioinformatics Resources and Tools by Users of Bioinformatics Centers in India meera yadav University of Delhi, [email protected] Manlunching Tawmbing Saha Institute of Nuclear Physisc, [email protected] Follow this and additional works at: http://digitalcommons.unl.edu/libphilprac Part of the Library and Information Science Commons yadav, meera and Tawmbing, Manlunching, "Use of Bioinformatics Resources and Tools by Users of Bioinformatics Centers in India" (2015). Library Philosophy and Practice (e-journal). 1254. http://digitalcommons.unl.edu/libphilprac/1254 Use of Bioinformatics Resources and Tools by Users of Bioinformatics Centers in India Dr Meera, Manlunching Department of Library and Information Science, University of Delhi, India [email protected], [email protected] Abstract Information plays a vital role in Bioinformatics to achieve the existing Bioinformatics information technologies. Librarians have to identify the information needs, uses and problems faced to meet the needs and requirements of the Bioinformatics users. The paper analyses the response of 315 Bioinformatics users of 15 Bioinformatics centers in India. The papers analyze the data with respect to use of different Bioinformatics databases and tools used by scholars and scientists, areas of major research in Bioinformatics, Major research project, thrust areas of research and use of different resources by the user. The study identifies the various Bioinformatics services and resources used by the Bioinformatics researchers. Keywords: Informaion services, Users, Inforamtion needs, Bioinformatics resources 1. Introduction ‘Needs’ refer to lack of self-sufficiency and also represent gaps in the present knowledge of the users. -
Scripting: Higher- Level Programming for the 21St Century
. John K. Ousterhout Sun Microsystems Laboratories Scripting: Higher- Cybersquare Level Programming for the 21st Century Increases in computer speed and changes in the application mix are making scripting languages more and more important for the applications of the future. Scripting languages differ from system programming languages in that they are designed for “gluing” applications together. They use typeless approaches to achieve a higher level of programming and more rapid application development than system programming languages. or the past 15 years, a fundamental change has been ated with system programming languages and glued Foccurring in the way people write computer programs. together with scripting languages. However, several The change is a transition from system programming recent trends, such as faster machines, better script- languages such as C or C++ to scripting languages such ing languages, the increasing importance of graphical as Perl or Tcl. Although many people are participat- user interfaces (GUIs) and component architectures, ing in the change, few realize that the change is occur- and the growth of the Internet, have greatly expanded ring and even fewer know why it is happening. This the applicability of scripting languages. These trends article explains why scripting languages will handle will continue over the next decade, with more and many of the programming tasks in the next century more new applications written entirely in scripting better than system programming languages. languages and system programming -
Challenges in Bioinformatics
Yuri Quintana, PhD, delivered a webinar in AllerGen’s Webinars for Research Success series on February 27, 2018, discussing different approaches to biomedical informatics and innovations in big-data platforms for biomedical research. His main messages and a hyperlinked index to his presentation follow. WHAT IS BIOINFORMATICS? Bioinformatics is an interdisciplinary field that develops analytical methods and software tools for understanding clinical and biological data. It combines elements from many fields, including basic sciences, biology, computer science, mathematics and engineering, among others. WHY DO WE NEED BIOINFORMATICS? Chronic diseases are rapidly expanding all over the world, and associated healthcare costs are increasing at an astronomical rate. We need to develop personalized treatments tailored to the genetics of increasingly diverse patient populations, to clinical and family histories, and to environmental factors. This requires collecting vast amounts of data, integrating it, and making it accessible and usable. CHALLENGES IN BIOINFORMATICS Data collection, coordination and archiving: These technologies have evolved to the point Many sources of biomedical data—hospitals, that we can now analyze not only at the DNA research centres and universities—do not have level, but down to the level of proteins. DNA complete data for any particular disease, due in sequencers, DNA microarrays, and mass part to patient numbers, but also to the difficulties spectrometers are generating tremendous of data collection, inter-operability -
Six Canonical Projects by Rem Koolhaas
5 Six Canonical Projects by Rem Koolhaas has been part of the international avant-garde since the nineteen-seventies and has been named the Pritzker Rem Koolhaas Architecture Prize for the year 2000. This book, which builds on six canonical projects, traces the discursive practice analyse behind the design methods used by Koolhaas and his office + OMA. It uncovers recurring key themes—such as wall, void, tur montage, trajectory, infrastructure, and shape—that have tek structured this design discourse over the span of Koolhaas’s Essays on the History of Ideas oeuvre. The book moves beyond the six core pieces, as well: It explores how these identified thematic design principles archi manifest in other works by Koolhaas as both practical re- Ingrid Böck applications and further elaborations. In addition to Koolhaas’s individual genius, these textual and material layers are accounted for shaping the very context of his work’s relevance. By comparing the design principles with relevant concepts from the architectural Zeitgeist in which OMA has operated, the study moves beyond its specific subject—Rem Koolhaas—and provides novel insight into the broader history of architectural ideas. Ingrid Böck is a researcher at the Institute of Architectural Theory, Art History and Cultural Studies at the Graz Ingrid Böck University of Technology, Austria. “Despite the prominence and notoriety of Rem Koolhaas … there is not a single piece of scholarly writing coming close to the … length, to the intensity, or to the methodological rigor found in the manuscript -
Technological Advancement in Object Oriented Programming Paradigm for Software Development
International Journal of Applied Engineering Research ISSN 0973-4562 Volume 14, Number 8 (2019) pp. 1835-1841 © Research India Publications. http://www.ripublication.com Technological Advancement in Object Oriented Programming Paradigm for Software Development Achi Ifeanyi Isaiah1, Agwu Chukwuemeka Odi2, Alo Uzoma Rita3, Anikwe Chioma Verginia4, Okemiri Henry Anaya5 1Department of Maths/Comp Sci/Stats/Info., Faculty of science, Alex Ekwueme University, Ndufu-Alike 2Department of Computer Science, Ebonyi State University-Abakaliki. 3Alex Ekwueme University, Ndufu-Alike, 4Department of Maths/Comp Sci/Stats/Info., Faculty of science, Alex Ekwueme University, Ndufu-Alike 5Department of Maths/Comp Sci/Stats/Info., Faculty of science, Alex Ekwueme University, Ndufu-Alike Abstract and personalization problems. Take for instance, a lot of sophisticated apps are being produced and release in the Object oriented programming paradigm in software market today through the application of OOP. Almost desktop development is one of the most popular methods in the apps are being converted to mobile apps through Java, C++, information technology industry and academia as well as in PHP & MySQL, R, Python etc platform which form the many other forms of engineering design. Software testimony of OOP in the software industries. Software development is a field of engineering that came into existence developer has been revolving using procedural language for owing to the various problems that developers of software the past decade before the advent of OOP. The relationships faced while developing software projects. This paper analyzes between them is that procedural languages focus on the some of the most important technological innovations in algorithm but OOP focuses on the object model itself, object oriented software engineering in recent times. -
Object Oriented Database Management Systems-Concepts
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Global Journal of Computer Science and Technology (GJCST) Global Journal of Computer Science and Technology: C Software & Data Engineering Volume 15 Issue 3 Version 1.0 Year 2015 Type: Double Blind Peer Reviewed International Research Journal Publisher: Global Journals Inc. (USA) Online ISSN: 0975-4172 & Print ISSN: 0975-4350 Object Oriented Database Management Systems-Concepts, Advantages, Limitations and Comparative Study with Relational Database Management Systems By Hardeep Singh Damesha Lovely Professional University, India Abstract- Object Oriented Databases stores data in the form of objects. An Object is something uniquely identifiable which models a real world entity and has got state and behaviour. In Object Oriented based Databases capabilities of Object based paradigm for Programming and databases are combined due remove the limitations of Relational databases and on the demand of some advanced applications. In this paper, need of Object database, approaches for Object database implementation, requirements for database to an Object database, Perspectives of Object database, architecture approaches for Object databases, the achievements and weakness of Object Databases and comparison with relational database are discussed. Keywords: relational databases, object based databases, object and object data model. GJCST-C Classification : F.3.3 ObjectOrientedDatabaseManagementSystemsConceptsAdvantagesLimitationsandComparativeStudywithRelationalDatabaseManagementSystems Strictly as per the compliance and regulations of: © 2015. Hardeep Singh Damesha. This is a research/review paper, distributed under the terms of the Creative Commons Attribution- Noncommercial 3.0 Unported License http://creativecommons.org/licenses/by-nc/3.0/), permitting all non-commercial use, distribution, and reproduction inany medium, provided the original work is properly cited.