Promises and Challenges of Systems Biology

2020 ◽  
Author(s):  
Srijani Chakraborty
Keyword(s):  
Systems Biology ◽  
Molecular Biology ◽  
Computer Science ◽  
And Mathematics ◽  
Engineering Physics

Modern systems biology is essentially interdisciplinary, tying molecular biology, the omics, bioinformatics and non-biological disciplines like computer science, engineering, physics, and mathematics together.

Computational Biology

2011 ◽  
pp. 641-646
Author(s):  
Andrew LaBrunda ◽  
Michelle LaBrunda
Keyword(s):  
Systems Biology ◽  
Molecular Biology ◽  
Computational Biology ◽  
Computer Science ◽  
Structure Prediction ◽  
Evolutionary Biology ◽  
Deterministic Model ◽  
Computational Genomics ◽  
Exact Moment ◽  
And Mathematics

It is impossible to pinpoint the exact moment at which computational biology became a discipline of its own, but one could say that it was in 1997 when the society of computational biology was formed. Regardless of its exact birthday, the research community has rapidly adopted computational biology and its applications are being vigorously explored. The study and application of medicine is a dynamic challenge. Changes in medicine usually take place as a result of new knowledge acquired through observation and experimentation. When a tamping rod 1-inch thick went through Phineas Gage’s head in 1848, his survival gave the medical field an unusual opportunity to observe behavior of a person missing their prefrontal cortex. This observation lead to the short-lived psychosurgical procedure known as a lobotomy, which attempted to change a person’s behavior by separating two portions of a person’s brain (Pols, 2001). Countless observations, experiments and mistakes represent how almost all medical knowledge has been acquired. The relatively new field of computational biology offers a nontraditional approach to contribute to the medical body of knowledge. Computational biology is a new field combining biology, computer science, and mathematics to solve problems that are unworkable with traditional biological techniques. It includes traditional areas such as systems biology, molecular biology, biochemistry, biophysics, statistics, and computer science, as well as recently developed disciplines including bioinformatics and computational genomics. Algorithms, which are able to closely model biological behavior, validate the medical understanding of the observed processes and can be used to model scenarios that might not be able to be physically reproduced. The goal of computational biology is to use mathematics and computer science to model biological systems on the molecular level. Instead of taking on large complex systems, computational biology is starting small, literally. Modeling problems in molecular biology and biochemistry is a far less daunting task. At a microscopic level, patient’s characteristics drop out of the equation and all information behavior affecting is known. This creates a deterministic model which, given the same input, will always produce the same output. Some of the major subdisciplines of computational biology are computational genomics, systems biology, protein structure prediction, and evolutionary biology, all of which model microscopic structures.

scholarly journals The use of Arduino software and hardware in a school physical experiment

2020 ◽  
Vol 54 (2) ◽  
pp. 122-133
Author(s):  
Vytaly M. Zadorozhnyi
Keyword(s):  
Computer Science ◽  
Integrated Approach ◽  
Laboratory Work ◽  
General Interest ◽  
Research Activity ◽  
Research Activities ◽  
Specialized School ◽  
And Mathematics ◽  
Physical Phenomena ◽  
Engineering Physics

The article considers the use of hardware and software Arduino in order to involve students in the study of such subjects as: physics and computer science; provide an opportunity improve and develop their own engineering ideas. The article proves that the use of hardware and software Arduino complex in teaching and research activity is an effective tool for improvement interest in such areas of activity as computer science, engineering, physics. The study found that an integrated approach allows arousing students’ interest in the study of natural sciences and mathematics, solving modern problems engineering and electronics, and developing them creativity. Work on your own projects allows children to show abilities and present their projects in various competitions, in addition motivates young researchers. Developed by students devices can significantly increase accuracy measurements during the experiment, increase the level of theoretical preparation for laboratory work, increase the general interest to perform laboratory work by students for due to the modernization of equipment and form new ones ideas about physical phenomena and processes. The results of students’ research activities can used during the teaching of physics in a specialized school, especially during school experiment.

Creating and Capturing Value through Crowdsourcing

2018 ◽  
Keyword(s):  
Information Systems ◽  
Systems Biology ◽  
Computer Science ◽  
Open Innovation ◽  
Product Innovation ◽  
Collective Intelligence ◽  
Innovation Management ◽  
Private And Public ◽  
Definition Of ◽  
The Uk

Examples of the value that can be created and captured through crowdsourcing go back to at least 1714, when the UK used crowdsourcing to solve the Longitude Problem, obtaining a solution that would enable the UK to become the dominant maritime force of its time. Today, Wikipedia uses crowds to provide entries for the world’s largest and free encyclopedia. Partly fueled by the value that can be created and captured through crowdsourcing, interest in researching the phenomenon has been remarkable. For example, the Best Paper Awards in 2012 for a record-setting three journals—the Academy of Management Review, Journal of Product Innovation Management, and Academy of Management Perspectives—were about crowdsourcing. In spite of the interest in crowdsourcing—or perhaps because of it—research on the phenomenon has been conducted in different research silos within the fields of management (from strategy to finance to operations to information systems), biology, communications, computer science, economics, political science, among others. In these silos, crowdsourcing takes names such as broadcast search, innovation tournaments, crowdfunding, community innovation, distributed innovation, collective intelligence, open source, crowdpower, and even open innovation. The book aims to assemble papers from as many of these silos as possible since the ultimate potential of crowdsourcing research is likely to be attained only by bridging them. The papers provide a systematic overview of the research on crowdsourcing from different fields based on a more encompassing definition of the concept, its difference for innovation, and its value for both the private and public sectors.

Teaching kinematics via arduino based STEM education material

2021 ◽  
Vol 57 (1) ◽  
pp. 015010
Author(s):  
Atakan Çoban ◽  
Mustafa Erol
Keyword(s):  
Time Dependence ◽  
Stem Education ◽  
Error Rate ◽  
Educational Environment ◽  
Two Dimensional ◽  
Education Material ◽  
Sample Application ◽  
And Mathematics ◽  
Engineering Physics ◽  
Physical Quantities

Abstract The present study reports an Arduino-based STEM education material that resolves the kinematics of a moving object, specifically focusing on two dimensional motion of the object. Throughout the work, a sample application that can be prepared in a classroom where students are active and including the acquisitions of Technology, Engineering, Physics and Mathematics in a single educational environment. In the study, instantaneous time dependence of the displacements, namely x(t) and y(t) components and the resultant R(t) component, are experimentally measured on a vehicle by using an Arduino UNO, distance sensors and Bluetooth sensor prepared within the scope of a STEM education approach. The ratios between those measured physical quantities and theoretical estimations are found to be %13.1 for the position, %1.4 for the velocity and %7.8 for the acceleration. The error rate of the data was accepted to be reasonable considering highly economical teaching materials.

scholarly journals Polynomials and General Degree-Based Topological Indices of Generalized Sierpinski Networks

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Chengmei Fan ◽  
M. Mobeen Munir ◽  
Zafar Hussain ◽  
Muhammad Athar ◽  
Jia-Bao Liu
Keyword(s):  
Complex Systems ◽  
Computer Science ◽  
Topological Indices ◽  
Fractal Nature ◽  
Similar Nature ◽  
Zagreb Index ◽  
Recursive Sequences ◽  
And Mathematics

Sierpinski networks are networks of fractal nature having several applications in computer science, music, chemistry, and mathematics. These networks are commonly used in chaos, fractals, recursive sequences, and complex systems. In this article, we compute various connectivity polynomials such as M -polynomial, Zagreb polynomials, and forgotten polynomial of generalized Sierpinski networks S k n and recover some well-known degree-based topological indices from these. We also compute the most general Zagreb index known as α , β -Zagreb index and several other general indices of similar nature for this network. Our results are the natural generalizations of already available results for particular classes of such type of networks.

scholarly journals Adaptation of the Core CDIO Standards 3.0 to STEM Higher Education

2021 ◽  
Vol 30 (2) ◽  
pp. 9-21
Author(s):  
A. I. Chuchalin
Keyword(s):  
Applied Sciences ◽  
Higher Education ◽  
Engineering Education ◽  
Computer Science ◽  
High Tech ◽  
The Core ◽  
Science Technology ◽  
Postgraduate Studies ◽  
Systematic Training ◽  
And Mathematics

It is proposed to adapt the new version of the internationally recognized standards for engineering education the Core CDIO Standards 3.0 to the programs of basic higher education in the field of technology, natural and applied sciences, as well as mathematics and computer science in the context of the evolution of STEM. The adaptation of the CDIO standards to STEM higher education creates incentives and contributes to the systematic training of specialists of different professions for coordinated teamwork in the development of high-tech products, as well as in the provision of comprehensive STEM services. Optional CDIO Standards are analyzed, which can be used selectively in STEM higher education. Adaptation of the CDIO-FCDI-FFCD triad to undergraduate, graduate and postgraduate studies in the field of science, technology, engineering and mathematics is considered as a mean for improving the system of three-cycle STEM higher education.

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