Search results for: computational biology

Authors: Jayson G. Balansag

Abstract:

An integrated biology and chemistry (iBC) course for freshmen college students was developed in University of Delaware. This course will prepare students to (1) become interdisciplinary thinkers in the field of biology and (2) collaboratively work with others from multiple disciplines in the future. This paper documents and describes the implementation of the course. The information gathered from reading literature, classroom observations, and interviews were used to carry out the purpose of this paper. The major goal of the iBC course is to align the concepts between Biology and Chemistry, so that students can draw science concepts from both disciplines which they can apply in their interdisciplinary researches. This course is offered every fall and spring semesters of each school year. Students enrolled in Biology are also enrolled in Chemistry during the same semester. The iBC is composed of lectures, laboratories, studio sessions, and workshops and is taught by the faculty from the biology and chemistry departments. In addition, the preceptors, graduate teaching assistants, and studio fellows facilitate the laboratory and studio sessions. These roles are interdependent with each other. The iBC can be used as a model for higher education institutions who wish to implement an integrated biology course.

Keywords: integrated biology and chemistry, integration, interdisciplinary research, new biology, undergraduate science education

Procedia PDF Downloads 218

Authors: Vishnu Pratap Singh Kirar, Madhuri Saxena

Abstract:

Advancement in sequence data generation technologies is churning out voluminous omics data and posing a massive challenge to annotate the biological functional features. With so much data available, the use of machine learning methods and tools to make novel inferences has become obvious. Machine learning methods have been successfully applied to a lot of disciplines, including computational biology and bioinformatics. Researchers in computational biology are interested to develop novel machine learning frameworks to classify the huge amounts of biological data. In this proposal, it plan to employ novel machine learning approaches to aid the understanding of how apparently innocuous mutations (in intergenic DNA and at synonymous sites) cause diseases. We are also interested in discovering novel functional sites in the genome and mutations in which can affect a phenotype of interest.

Keywords: genome wide association studies (GWAS), next generation sequencing (NGS), deep learning, omics

Procedia PDF Downloads 63

Authors: Fatemeh Nokhodchi Bonab

Abstract:

Bioinformatics, in its broad sense, involves application of computer processes to solve biological problems. A wide range of computational tools are needed to effectively and efficiently process large amounts of data being generated as a result of recent technological innovations in biology and medicine. A number of computational tools have been developed or adapted to deal with the experimental riches of complex and multivariate data and transition from data collection to information or knowledge. These bioinformatics tools are being evaluated and applied in various medical areas including early detection, risk assessment, classification, and prognosis of cancer. The goal of these efforts is to develop and identify bioinformatics methods with optimal sensitivity, specificity, and predictive capabilities. The recent flood of data from genome sequences and functional genomics has given rise to new field, bioinformatics, which combines elements of biology and computer science. Bioinformatics is conceptualizing biology in terms of macromolecules (in the sense of physical-chemistry) and then applying "informatics" techniques (derived from disciplines such as applied maths, computer science, and statistics) to understand and organize the information associated with these molecules, on a large-scale. Here we propose a definition for this new field and review some of the research that is being pursued, particularly in relation to transcriptional regulatory systems.

Keywords: methods, applications, transcriptional regulatory systems, techniques

Procedia PDF Downloads 95

Authors: Ibraheem Alzahrani

Abstract:

The Saudi Arabia ministry of higher education has established 24 universities across various cities in the kingdom. The universities have the mandate of sustaining technological progress in both teaching and learning. The present study explores the statues of teaching in Saudi universities, focusing on biology, a critical curriculum. The paper explores biology teachers’ points of view is several Saudi higher education institutions through questionnaires disseminated via emails. According to the findings, the current teaching methods are traditional and the teachers believe that it is critical to change it. This study also, reviews how biology has been taught in the kingdom over the past, as well as how it is undertaken presently. In addition, some aspects of biology teaching are considered, including the biology curriculum and learning objectives in higher education biology.

Keywords: higher education, teaching style, traditional learning, electronic learning, web 2.0 applications, blended learning

Procedia PDF Downloads 352

Authors: N. Nor Azman, M. F. Kamarudin, S. I. Ong, N. Maaulot

Abstract:

PERMATApintar^® National Gifted Center is, to the author’s best of knowledge, the first center in Malaysia that provides a platform for Malaysian talented students with high ability in thinking. This center has built a teaching and learning biology curriculum that suits the ability of these gifted students. The level of PERMATApintar^® biology curriculum is basically higher than the national biology curriculum. Here, the foundation students are exposed to the PERMATApintar^® biology curriculum at the age of as early as 11 years old. This center practices a 4-time-a-year examination system to monitor the academic performances of the students. Generally, most of the time, male students show no or low interest towards biology subject compared to female students. This study is to investigate the association of students’ gender and their academic performances in biology examination. A total of 39 students’ scores in twelve sets of biology examinations in 3 years have been collected and analyzed by using the statistical analysis. Based on the analysis, there are no significant differences between male and female students against the biology academic performances with a significant level of p = 0.05. This indicates that gender is not associated with the scores of biology examinations among the students. Another result showed that the average score for male studenta was higher than the female students. Future research can be done by comparing the biology academic achievement in Malaysian National Examination (Sijil Pelajaran Malaysia, SPM) between the Foundation 3 students (Grade 9) and Level 2 students (Grade 11) with similar PERMATApintar^® biology curriculum.

Keywords: academic performances, biology, gender differences, gifted students,

Procedia PDF Downloads 211

Authors: Javed Mohammed

Abstract:

Right now, bio-medical infrastructure lags well behind the curve. Our healthcare system is dispersed and disjointed; medical records are a bit of a mess; and we do not yet have the capacity to store and process the crazy amounts of data coming our way from widespread whole-genome sequencing. And then there are privacy issues. Despite these infrastructure challenges, some researchers are plunging into bio medical Big Data now, in hopes of extracting new and actionable knowledge. They are doing delving into molecular-level data to discover bio markers that help classify patients based on their response to existing treatments; and pushing their results out to physicians in novel and creative ways. Computer scientists and bio medical researchers are able to transform data into models and simulations that will enable scientists for the first time to gain a profound under-standing of the deepest biological functions. Solving biological problems may require High-Performance Computing HPC due either to the massive parallel computation required to solve a particular problem or to algorithmic complexity that may range from difficult to intractable. Many problems involve seemingly well-behaved polynomial time algorithms (such as all-to-all comparisons) but have massive computational requirements due to the large data sets that must be analyzed. High-throughput techniques for DNA sequencing and analysis of gene expression have led to exponential growth in the amount of publicly available genomic data. With the increased availability of genomic data traditional database approaches are no longer sufficient for rapidly performing life science queries involving the fusion of data types. Computing systems are now so powerful it is possible for researchers to consider modeling the folding of a protein or even the simulation of an entire human body. This research paper emphasizes the computational biology's growing need for high-performance computing and Big Data. It illustrates this article’s indispensability in meeting the scientific and engineering challenges of the twenty-first century, and how Protein Folding (the structure and function of proteins) and Phylogeny Reconstruction (evolutionary history of a group of genes) can use HPC that provides sufficient capability for evaluating or solving more limited but meaningful instances. This article also indicates solutions to optimization problems, and benefits Big Data and Computational Biology. The article illustrates the Current State-of-the-Art and Future-Generation Biology of HPC Computing with Big Data.

Keywords: high performance, big data, parallel computation, molecular data, computational biology

Procedia PDF Downloads 337

Authors: Ayeni Margaret Foluso, K. A. Omotayo

Abstract:

This study investigated the impact of selected environmental variables as determinants of students’ achievements in biology in secondary schools. The selected environmental variables are class size and laboratory adequacy. The purpose was to find out whether these environmental variables can bring about improvement in the learning of biology by Senior Secondary School Students. The study design used was descriptive research of the survey type. Two instruments were used that is, Biology Achievement Test and School Environment Questionnaire .The population of the study consisted of all Biology students in both public and private Senior Secondary Schools class III (SSIII) in all the three selected states in South West Nigeria. A sample of 900 Biology students and 45 Biology Teachers from both public and private Senior Secondary Schools Class III were used. Two research hypotheses were generated for the study. The data collected were subjected to both descriptive statistics of mean and standard deviation; and the inferential statistics of regression Analyses was employed to test the hypotheses formulated. From the results, it was revealed that the selected environmental variables had influence on the students’ achievement in biology.

Keywords: environmental variables, determinants, students’ achievement, school science

Procedia PDF Downloads 449

Authors: Stephanie Boue, Nicolas Sierro, Julia Hoeng, Manuel C. Peitsch

Abstract:

Systems biology relies on large numbers of data points and sophisticated methods to extract biologically meaningful signal and mechanistic understanding. For example, analyses of transcriptomics and proteomics data enable to gain insights into the molecular differences in tissues exposed to diverse stimuli or test items. Whereas the interpretation of endpoints specifically measuring a mechanism is relatively straightforward, the interpretation of big data is more complex and would benefit from comparing results obtained with diverse analysis methods. The sbv IMPROVER project was created to implement solutions to verify systems biology data, methods, and conclusions. Computational challenges leveraging the wisdom of the crowd allow benchmarking methods for specific tasks, such as signature extraction and/or samples classification. Four challenges have already been successfully conducted and confirmed that the aggregation of predictions often leads to better results than individual predictions and that methods perform best in specific contexts. Whenever the scientific question of interest does not have a gold standard, but may greatly benefit from the scientific community to come together and discuss their approaches and results, datathons are set up. The inaugural sbv IMPROVER datathon was held in Singapore on 23-24 September 2016. It allowed bioinformaticians and data scientists to consolidate their ideas and work on the most promising methods as teams, after having initially reflected on the problem on their own. The outcome is a set of visualization and analysis methods that will be shared with the scientific community via the Garuda platform, an open connectivity platform that provides a framework to navigate through different applications, databases and services in biology and medicine. We will present the results we obtained when analyzing data with our network-based method, and introduce a datathon that will take place in Japan to encourage the analysis of the same datasets with other methods to allow for the consolidation of conclusions.

Keywords: big data interpretation, datathon, systems toxicology, verification

Procedia PDF Downloads 258

Authors: Sy Ing Ong, N. Norazman, H. W. You, A. Zahidi, R. Ahmad Faisal

Abstract:

The decline in students’ involvement in the fields of Science, Technology, Engineering and Mathematics (STEM) worldwide is alarming. In Malaysia, this scenario also draws the attention of Ministry of Education due to the high demand for professionals in STEM industries and for the sake of country development. Intensive researches have been done worldwide to identify the best solution to improve the enrolment of students in science studies. Attitude is being identified as one of the key factors that will influence students’ interest and achievement in academic. Male students are always associated with negative attitudes compared to female students towards the study of Biological science. Hence, this study investigates the attitudes of students towards Biology in the setting of an academic talented institution in Malaysia namely ASASIpintar Pre-University Programme. A total of 84 students were randomly selected from 127 students as the samples of this study. The instrument of Biology Attitude Scale (BAS) from Russell and Hollander (1975) was used to identify the attitudes of samples. Based on the analysis, there was no significant difference in the students’ mean attitude towards Biology subject in this institution between genders with a significant level of p = 0.05. This indicated that gender is not a key factor that influences students’ attitude towards Biology in this study. Future research can be done on other factors that will contribute to the attitude of students towards biology in Malaysia, especially for academically talented students.

Keywords: academic talented, attitude, biology, gender

Procedia PDF Downloads 186

Authors: Waheed Akhtar

Abstract:

In the current study, we aim to access the different month-wise reproductive biology of S. esocinus. Samples were collected from Rive Swat in the period of March 2022 to March 2023. Samples were collected using different gills nets of different sizes. Gonado Somatic Index and fecundity were studied using gravimetric to identify the breeding season and reproductive potential. The highest GSI was recorded in the month of April and November. Male to female ratio was in balance. The weight of the fish, size of the fish and ovary were parallel to the fecundity. This is the baseline study for the breeding biology of S. esocinus and further molecular study is required to identify the internal and external factors associated with the breeding biology of S. esocinus.

Keywords: snow trout, length and weight relationship, fecundity, river Swat

Procedia PDF Downloads 47

Authors: Abdullahi Garba

Abstract:

The study investigated the effects of practical activities on performance among biology students in Zaria education zone, Kaduna State, Nigeria. The population consists of 18 public schools in the Zaria Education Zone with a total number of 4,763 students. A random sample of 115 students was selected from the population in the study area. The study design was quasi-experimental, which adopted the pre-test, post-test experimental, and control group design. The experimental group was exposed to practical activities, while the control group was taught with the lecture method. A validated instrument, a biology performance test (BPT) with a reliability coefficient of 0.82, was used to gather data which were analyzed using a t-test and paired sample t-test. Two research questions and hypotheses guided the study. The hypotheses were tested at p≤0.05 level of significance. Findings revealed that: there was a significant difference in the academic performance of students exposed to practical activities compared to their counterparts; there was no significant difference in performance between male and female Biology students exposed to practical activities. The recommendation given was that practical activities should be encouraged in the teaching and learning of Biology for better understanding. The Federal and State Ministry of Education should sponsor biology teachers for training and retraining of teachers to improve the academic performance of students in the subject.

Keywords: biology, practical, activity, performance

Procedia PDF Downloads 51

Authors: Piotr J. Balwierz, Mikhail Pachkov, Phil Arnold, Andreas J. Gruber, Mihaela Zavolan, Erik van Nimwegen

Abstract:

Understanding the key players and interactions in the regulatory networks that control gene expression and chromatin state across different cell types and tissues in metazoans remains one of the central challenges in systems biology. Our laboratory has pioneered a number of methods for automatically inferring core gene regulatory networks directly from high-throughput data by modeling gene expression (RNA-seq) and chromatin state (ChIP-seq) measurements in terms of genome-wide computational predictions of regulatory sites for hundreds of transcription factors and micro-RNAs. These methods have now been completely automated in an integrated webserver called ISMARA that allows researchers to analyze their own data by simply uploading RNA-seq or ChIP-seq data sets and provides results in an integrated web interface as well as in downloadable flat form. For any data set, ISMARA infers the key regulators in the system, their activities across the input samples, the genes and pathways they target, and the core interactions between the regulators. We believe that by empowering experimental researchers to apply cutting-edge computational systems biology tools to their data in a completely automated manner, ISMARA can play an important role in developing our understanding of regulatory networks across metazoans.

Keywords: gene expression analysis, high-throughput sequencing analysis, transcription factor activity, transcription regulation

Procedia PDF Downloads 33

Authors: Narupot Putwattana

Abstract:

Changes in global situation such as environmental and economic crisis brought the new perspective for science education called integrative biology. STEM has been increasingly mentioned for several educational researches as the approach which combines the concept in Science (S), Technology (T), Engineering (E) and Mathematics (M) to apply in teaching and learning process so as to strengthen the 21st-century skills such as creativity and critical thinking. Recent studies demonstrated STEM as the pedagogy which described the engineering process along with the science classroom activities. So far, pedagogical contents for STEM explaining the content in biology have been scarce. A qualitative literature review was conducted so as to gather the articles based on electronic databases (google scholar). STEM education, engineering design, teaching and learning of biology were used as main keywords to find out researches involving with the application of STEM in biology teaching and learning process. All articles were analyzed to obtain appropriate teaching and learning model that unify the core concept of biology. The synthesized model comprised of engineering design, inquiry-based learning, biological prototype and biologically-inspired design (BID). STEM content and context integration were used as the theoretical framework to create the integrative biology instructional model for STEM education. Several disciplines contents such as biology, engineering, and technology were regarded for inquiry-based learning to build biological prototype. Direct and indirect integrations were used to provide the knowledge into the biology related STEM strategy. Meanwhile, engineering design and BID showed the occupational context for engineer and biologist. Technological and mathematical aspects were required to be inspected in terms of co-teaching method. Lastly, other variables such as critical thinking and problem-solving skills should be more considered in the further researches.

Keywords: biomimicry, engineering approach, STEM education, teaching and learning model

Procedia PDF Downloads 219

Authors: Mukhtarkhanova Ainagul Madievna, Imanbek Karakoz

Abstract:

The development and implementation of active forms and methods of extracurricular work in biology are carried out, assistance to people in determining sustainable interests in a particular field of science, expanding pupil's knowledge and horizons during in–depth study of program issues that go beyond the curriculum where considered, but accessible to the understanding of people; the development of interest in the subject, independence, creative activity. The purpose of this study is to open interest through extracurricular activities for teaching biology. The purpose of the presented work is to arouse people's interest in biology lessons in the modern world through extracurricular activities. First, the level of people was determined in the traditional style of teaching lessons, for which special tests and evaluation criteria were compiled. The level of pupils' knowledge of biology was determined by a questionnaire. Samples of extracurricular work were presented, and practices were conducted in the educational process. At the next stage, the level of pupils after the experiment was compared. The results of the work were discussed, and recommendations were developed.

Keywords: extracurricular activities, modern world, teaching, method, excursions, laboratory experiments, science fairs

Procedia PDF Downloads 49

Authors: Helen Ngozi Ibe, Chimmuanya Ezere

Abstract:

The study investigated the effect of Question Answer Relationships (QARs) in science reading on secondary school students’ achievement in Biology in Owerri Education Zone II of Imo State. The study adopted a quasi-experimental design and was guided by two research questions and two hypotheses. The sample comprised of 67 SS2 Biology students. The sample was drawn using random sampling technique. One researcher made instrument titled: Biology Achievement Test (BAT) was used for collecting the data of the study. The reliability of the instrument was established using Kuder Richardson formula (KR-20) which yielded a reliability index of 0.85 and Cronbach alpha for the BSIRS with an index of 0.71. Research questions were answered using mean and standard deviation. T-test statistics was used to test the hypotheses at 0.05 level of significance. The major findings are that students exposed to QARs strategy in science reading had higher achievement mean scores in biology than students in the control group; there is no significant difference between the achievement mean scores of male and female students exposed to QARs. The researchers recommended that science teachers should teach students the Question Answer Relationship reading strategy and that science students should endeavour to use the question - answer relationship reading strategy in classroom and individual science reading in order to enhance high academic achievement in the subjects being read.

Keywords: academic achievement, biology, science reading, question-answer relationship

Procedia PDF Downloads 87

Authors: Nik Azmah Nik Yusuff, Faridah Hassan Basri, Rosnidar Mansor

Abstract:

The purpose of the study is to find out the effectiveness of using Graphic calculators (GC) with Calculator Based Laboratory 2 (CBL2) in teaching and learning of form four biology for these topics: Nutrition, Respiration and Dynamic Ecosystem. Sixty form four science stream students were the participants of this study. The participants were divided equally into the treatment and control groups. The treatment group used GC with CBL2 during experiments while the control group used the ordinary conventional laboratory apparatus without using GC with CBL2. Instruments in this study were a set of pre-test and post-test and a questionnaire. T-Test was used to compare the student’s biology achievement while a descriptive statistic was used to analyze the outcome of the questionnaire. The findings of this study indicated the use of GC with CBL2 in biology had significant positive effect. The highest mean was 4.43 for item stating the use of GC with CBL2 had saved collecting experiment result’s time. The second highest mean was 4.10 for item stating GC with CBL2 had saved drawing and labelling graphs. The outcome from the questionnaire also showed that GC with CBL2 were easy to use and save time. Thus, teachers should use GC with CBL2 in support of efforts by Malaysia Ministry of Education in encouraging technology-enhanced lessons.

Keywords: biology experiments, Calculator-Based Laboratory 2 (CBL2), graphic calculators, Malaysia Secondary School, teaching/learning

Procedia PDF Downloads 379

Authors: Mintu Philip, Renumol V. G.

Abstract:

An introductory programming course is a major challenge faced in Computing Education. Many of the introductory programming courses fail because student concentrate mainly on writing programs using a programming language rather than involving in problem solving. Computational thinking is a general approach to solve problems. This paper proposes a new preliminary course that aims to develop computational thinking skills in students, which may help them to become good programmers. The proposed course is designed based on the four basic components of computational thinking - abstract thinking, logical thinking, modeling thinking and constructive thinking. In this course, students are engaged in hands-on problem solving activities using a new problem solving model proposed in this paper.

Keywords: computational thinking, computing education, abstraction, constructive thinking, modelling thinking

Procedia PDF Downloads 419

Authors: Janneth Gonzalez, Marco Avila, George Barreto

Abstract:

GRP78 participates in multiple functions in the cell during normal and pathological conditions, controlling calcium homeostasis, protein folding and unfolded protein response. GRP78 is located in the endoplasmic reticulum, but it can change its location under stress, hypoxic and apoptotic conditions. NF-κB represents the keystone of the inflammatory process and regulates the transcription of several genes related with apoptosis, differentiation, and cell growth. The possible relationship between GRP78-NF-κB could support and explain several mechanisms that may regulate a variety of cell functions, especially following brain injuries. Although several reports show interactions between NF-κB and heat shock proteins family members, there is a lack of information on how GRP78 may be interacting with NF-κB, and possibly regulating its downstream activation. Therefore, we assessed the computational predictions of the GRP78 (Chain A) and NF-κB complex (IkB alpha and p65) protein-protein interactions. The interaction interface of the docking model showed that the amino acids ASN 47, GLU 215, GLY 403 of GRP78 and THR 54, ASN 182 and HIS 184 of NF-κB are key residues involved in the docking. The electrostatic field between GRP78-NF-κB interfaces and molecular dynamic simulations support the possible interaction between the proteins. In conclusion, this work shed some light in the possible GRP78-NF-κB complex indicating key residues in this crosstalk, which may be used as an input for better drug design strategy targeting NF-κB downstream signaling as a new therapeutic approach following brain injuries.

Keywords: computational biology, protein interactions, Grp78, bioinformatics, molecular dynamics

Procedia PDF Downloads 320

Authors: Keerthi S. Shetty, Annappa Basava

Abstract:

In recent years, modelling of biological systems represented by biochemical reactions has become increasingly important in Systems Biology. Biological systems represented by biochemical reactions are highly stochastic in nature. Probabilistic model is often used to describe such systems. One of the main challenges in Systems biology is to combine absolute experimental data into probabilistic model. This challenge arises because (1) some molecules may be present in relatively small quantities, (2) there is a switching between individual elements present in the system, and (3) the process is inherently stochastic on the level at which observations are made. In this paper, we describe a novel idea of combining absolute experimental data into probabilistic model using tool R2. Through a case study of the Transcription Process in Prokaryotes we explain how biological systems can be written as probabilistic program to combine experimental data into the model. The model developed is then analysed in terms of intrinsic noise and exact sampling of switching times between individual elements in the system. We have mainly concentrated on inferring number of genes in ON and OFF states from experimental data.

Keywords: systems biology, probabilistic model, inference, biology, model

Procedia PDF Downloads 314

Authors: Wei Sun, Yan Dong

Abstract:

There is an increasing interest in introducing computational thinking at an early age. Computational thinking, like mathematical thinking, engineering thinking, and scientific thinking, is a kind of analytical thinking. Learning computational thinking skills is not only to improve technological literacy, but also allows learners to equip with practicable skills such as problem-solving skills. As people realize the importance of computational thinking, the field of educational technology faces a problem: how to choose appropriate tools and activities to help students develop computational thinking skills. Robots are gradually becoming a popular teaching tool, as robots provide a tangible way for young children to access to technology, and controlling a robot through programming offers them opportunities to engage in developing computational thinking. This study explores whether the introduction of flowcharts into the robotics programming courses can help children convert natural language into a programming language more easily, and then to better cultivate their computational thinking skills. An experimental study was adopted with a sample of children ages six to seven (N = 16) participated, and a one-meter-tall humanoid robot was used as the teaching tool. Results show that children can master basic programming concepts through robotic courses. Children's computational thinking has been significantly improved. Besides, results suggest that flowcharts do have an impact on young children’s computational thinking skills development, but it only has a significant effect on the "sequencing" and "correspondence" skills. Overall, the study demonstrates that the humanoid robot and flowcharts have qualities that foster young children to learn programming and develop computational thinking skills.

Keywords: robotics, computational thinking, programming, young children, flow chart

Procedia PDF Downloads 119

Authors: Boris Melnikov, Ye Zhang, Dmitrii Chaikovskii

Abstract:

We continue to consider one of the cybernetic methods in computational biology related to the study of DNA chains. Namely, we are considering the problem of reconstructing the not fully filled distance matrix of DNA chains. When applied in a programming context, it is revealed that with a modern computer of average capabilities, creating even a small-sized distance matrix for mitochondrial DNA sequences is quite time-consuming with standard algorithms. As the size of the matrix grows larger, the computational effort required increases significantly, potentially spanning several weeks to months of non-stop computer processing. Hence, calculating the distance matrix on conventional computers is hardly feasible, and supercomputers are usually not available. Therefore, we started publishing our variants of the algorithms for calculating the distance between two DNA chains; then, we published algorithms for restoring partially filled matrices, i.e., the inverse problem of matrix processing. In this paper, we propose an algorithm for restoring the distance matrix for DNA chains, and the primary focus is on enhancing the algorithms that shape the greedy function within the branches and boundaries method framework.

Keywords: DNA chains, distance matrix, optimization problem, restoring algorithm, greedy algorithm, heuristics

Procedia PDF Downloads 72

Authors: I. A. Libata

Abstract:

The present study was carried out to determine the attitudes of Secondary School Students towards Biology in Birnin Kebbi metropolis. The population of the study is 2680 SS 2 Secondary School Students in Birnin Kebbi metropolis. Proportionate random sampling was used in selecting the samples. Oppinnionnaire was the only instrument used in the study. The instrument was subjected to test-retest reliability. The reliability index of the instrument was 0.69. Overall scores of the Students were analyzed and a mean score was determined, the mean score of students was 85. There were no significant differences between the attitudes of male and female students. The results also revealed that there was significant difference between the attitude of science and art students. The results also revealed that there was significant difference between the attitude of public and private school students. The study also reveals that majority of students in Birnin Kebbi Metropolis have positive attitudes towards biology. Based on the findings of this study, the researcher recommended that teachers should motivate students, which they can do through their teaching styles and by showing them the relevance of the learning topics to their everyday lives. Government and the school management should create the learning environment that helps motivate students not only to come to classes but also want to learn and enjoy learning Biology.

Keywords: attitudes, students, Birnin-Kebbi, metropolis

Procedia PDF Downloads 365

Authors: Hassan M. H. Mustafa

Abstract:

This piece of research addresses an interesting comparative analytical study. Which considers two concepts of diverse algorithmic computational intelligence approaches related tightly with Neural and Non-Neural Systems. The first algorithmic intelligent approach concerned with observed obtained practical results after three neural animal systems’ activities. Namely, they are Pavlov’s, and Thorndike’s experimental work. Besides a mouse’s trial during its movement inside figure of eight (8) maze, to reach an optimal solution for reconstruction problem. Conversely, second algorithmic intelligent approach originated from observed activities’ results for Non-Neural Ant Colony System (ACS). These results obtained after reaching an optimal solution while solving Traveling Sales-man Problem (TSP). Interestingly, the effect of increasing number of agents (either neurons or ants) on learning performance shown to be similar for both introduced systems. Finally, performance of both intelligent learning paradigms shown to be in agreement with learning convergence process searching for least mean square error LMS algorithm. While its application for training some Artificial Neural Network (ANN) models. Accordingly, adopted ANN modeling is a relevant and realistic tool to investigate observations and analyze performance for both selected computational intelligence (biological behavioral learning) systems.

Keywords: artificial neural network modeling, animal learning, ant colony system, traveling salesman problem, computational biology

Procedia PDF Downloads 444

Authors: Luanna B. Prevost, Kelli Carter, Margaurete Romero, Kirsti Martinez

Abstract:

Writing is an essential scientific practice, yet, in several countries, the increasing university science class-size limits the use of written assessments. Written assessments allow students to demonstrate their learning in their own words and permit the faculty to evaluate students’ understanding. However, the time and resources required to grade written assessments prohibit their use in large-enrollment science courses. This study examined the use of machine learning algorithms to automatically analyze student writing and provide timely feedback to the faculty about students' writing in biology. Written responses to questions about matter and energy transformation were collected from large-enrollment undergraduate introductory biology classrooms. Responses were analyzed using the LightSide text mining and classification software. Cohen’s Kappa was used to measure agreement between the LightSide models and human raters. Predictive models achieved agreement with human coding of 0.7 Cohen’s Kappa or greater. Models captured that when writing about matter-energy transformation at the ecosystem level, students focused on primarily on the concepts of heat loss, recycling of matter, and conservation of matter and energy. Models were also produced to capture writing about processes such as decomposition and biochemical cycling. The models created in this study can be used to provide automatic feedback about students understanding of these concepts to biology faculty who desire to use formative written assessments in larger enrollment biology classes, but do not have the time or personnel for manual grading.

Keywords: machine learning, written assessment, biology education, text mining

Procedia PDF Downloads 249

Authors: Faruque Miah, Hafij Ali, Enaya Jannat, Tanmoy Modok Shuvra, M. Niamul Naser

Abstract:

In this study, breeding biology and induced breeding of freshwater mud eel, Monopterus cuchia was observed during the experimental period from February to June, 2013. Breeding biology of freshwater mud eel, Monopterus cuchia was considered in terms of gonadosomatic index, length-weight relationship of gonad, ova diameter and fecundity. The ova diameter was recorded from 0.3 mm to 4.30 mm and the individual fecundity was recorded from 155 to 1495 while relative fecundity was found from 2.64 to 12.45. The fecundity related to body weight and length of fish was also discussed. A peak of GSI was observed 2.14±0.2 in male and 5.1 ±1.09 in female. Induced breeding of freshwater mud eel, Monopterus cuchia was also practiced with different doses of different inducing agents like pituitary gland (PG), human chorionic gonadotropin (HCG), Gonadotropin releasing hormone (GnRH) and Ovuline-a synthetic hormone in different environmental conditions. However, it was observed that the artificial breeding of freshwater mud eel, Monopterus cuchia was not yet succeeded through inducing agents in captive conditions, rather the inducing agent showed negative impacts on fecundity and ovarian tissues. It was seen that mature eggs in the oviduct were reduced, absorbed and some eggs were found in spoiled condition.

Keywords: breeding biology, induced breeding, Monopterus cuchia, human chorionic gonadotropin

Procedia PDF Downloads 744

Authors: Ilse Kreme

Abstract:

To the best of this author’s knowledge, no studies have been identified on the connection between a refusal to engage in health-protective behaviors and a basic understanding of viral biology among community college students, faculty, and staff during the COVID-19 pandemic. Lack of scientific knowledge could prevent understanding of why these behaviors are important to prevent the community spread of COVID-19, even when they are not shown to offer much individual protection. In this study, a possible correlation was examined between a basic knowledge level of viral disease that comes from having taken a college biology course and disease perceptions of COVID-19. In particular, disease risk perception, disease severity percept and mask-wearing behaviors were examined as they correlated with having taken an undergraduate biology course. The effect of covariates of age, gender, and education level were investigated along with the main dependent variables. A representative sample of the population included students, faculty, and staff at Paradise Valley Community College (PVCC) in Phoenix, Arizona. Participants were recruited by an email sent to all students, faculty, and staff at PVCC using an all-college email distribution. Disease risk and severity perception were assessed with the Brief Illness Perception Questionnaire 5 (BIP-Q5), which was modified to include questions measuring participant age, education level, and whether they took or ever took a college biology course. Two additional questions measured compliance of willingness to wear a face mask. The results showed an effect of gender on mask-wearing behavior and a correlation between having taken a biology course and disease severity perception. No differences were seen in mask-wearing behavior and disease risk perception as a result of having taken a biology course. These findings suggest that taking an undergraduate biology course leads to a greater awareness of COVID-19 disease severity through an understanding of the basic biological principles of viral disease transmission. The results can be used to modify existing health education strategies. Further research is needed on how to best reach target audiences in all education brackets.

Keywords: COVID-19, education, gender, mask wearing, disease risk perception, disease severity perception

Procedia PDF Downloads 76

Authors: Shivani Sharma, Prashant Saxena, Inamul Hasan Madar

Abstract:

Since the time of Darwin, it has been considered that genetic change is the direct indicator of variation in phenotype. But a few studies in system biology in the past years have proposed that epigenetic developmental processes also affect the phenotype thus shifting the focus from a linear genotype-phenotype map to a non-linear G-P map. In this paper, we attempt at explaining the evolution of colour vision in mammals by taking LWS/ Long-wave sensitive gene under consideration.

Keywords: evolution, phenotypes, epigenetics, LWS gene, G-P map

Procedia PDF Downloads 483

Authors: N. Dahbi, M. Daoudi

Abstract:

This paper deals with the use of computational method based on Monte Carlo simulation in order to investigate the transport phenomena of the electron in HgCdTe narrow band gap semiconductor. Via this method we can evaluate the time dependence of the transport parameters: velocity, energy and mobility of electrons through matter (HgCdTe).

Keywords: Monte Carlo, transport parameters, HgCdTe, computational mechanics

Procedia PDF Downloads 447

Authors: Tomokazu Shirai, Akihiko Kondo

Abstract:

Technologies of metabolic engineering or synthetic biology are essential for effective microbial bioproduction. It is especially important to develop an in silico tool for designing a metabolic pathway producing an unnatural and valuable chemical such as fossil materials of fuel or plastics. We here demonstrated two in silico tools for designing novel metabolic pathways: BioProV and HyMeP. Furthermore, we succeeded in creating an artificial metabolic pathway by enzyme engineering.

Keywords: bioinformatics, metabolic engineering, synthetic biology, genome scale model

Procedia PDF Downloads 313

Authors: Sul-Ah Ahn, Youngim Jung

Abstract:

The research activities of the computational scientists using high-performance computing are analyzed using bibliometric approaches. This study aims at providing computational scientists using high-performance computing and relevant policy planners with useful bibliometric results for an assessment of research activities. In order to achieve this purpose, we carried out a co-authorship network analysis of journal articles to assess the research activities of computational scientists using high-performance computing as a case study. For this study, we used journal articles of the Scopus database from Elsevier covering the time period of 2006-2015. We extracted the author rank in the computational science field using high-performance computing by the number of papers published during ten years from 2006. Finally, we drew the co-authorship network for 50 top-authors and their coauthors and described some features of the co-authorship network in relation to the author rank. Suggestions for further studies are discussed.

Keywords: co-authorship network analysis, computational science, high performance computing, research activity

Procedia PDF Downloads 284