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ICCBB '18: Proceedings of the 2018 2nd International Conference on Computational Biology and Bioinformatics
ACM2018 Proceeding
Publisher:
  • Association for Computing Machinery
  • New York
  • NY
  • United States
Conference:
ICCBB 2018: 2018 2nd International Conference on Computational Biology and Bioinformatics Bari Italy October 11 - 13, 2018
ISBN:
978-1-4503-6552-9
Published:
11 October 2018

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Abstract

The 2018 2nd International Conference on Computational Biology and Bioinformatics (ICCBB 2018) was successfully held in Bari, Italy during October 11-13, 2018. With the supports of Polytechnic University of Bari and Hong Kong Chemical, Biological & Environmental Engineering Society (CBEES), the conference brought together researchers, engineers, academicians as well as industrial professionals from all over the world to share their experience and research findings in Computational Biology and Bioinformatics.

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SESSION: Biotechnology and Information Medicine
research-article
Fractional Order Modeling and Control of a Carrier Prototype for Targeted Drug Delivery

This paper tackles the field of applied control engineering in the nanomedical field, both in terms of modeling and control of the dynamics of a scalable robot transiting a vascular environment. An experimental fractional order model is obtained that ...

research-article
A Simple SIR Mathematical Model of Malaria Transmission with the Efficacy of the Vaccine

The main objective of this paper is to analyze dynamics of malaria disease transmission for the human and mosquito populations, by including the impact of malaria transmission from mother to baby before or during birth (vertical transmission) and ...

research-article
Knowledge, Attitudes and Practices Towards Seasonal Influenza and Vaccine among Private High School Students in Connecticut

Background: The United States suffered from its worst influenza season since 2009 during the winter of 2017-2018. High school is prone to influenza outbreak due to the high density of students and close social spaces. In order to understand the weak ...

research-article
Properties for Hesitant Information Sets

The concept of information sets is inspired by the way we perceive information source values. However, they lack a provision to represent the hesitancy inevitably associated with the perceived values. To this end, recently the concept of hesitant ...

research-article
Analysis of High-Risk Human Papillomavirus Using Decision Tree and Apriori Algorithm

Human Papillomaviruses (HPV) are small, nonenveloped, double-stranded DNA and function as pathogens that infect epithelial surfaces of humans and animals. Undetected and left not treated, HPV can develop into cervical cancer. This study aims to ...

research-article
Ergonomic Pillow for Indonesian Anthropometry: A Project Pilot Study

Sleep is a natural cycle for human for discharging fatigue and recovery process. To ensure a better sleep quality, we need a pillow that can suit our body part and bring comfortability, or called ergonomics pillow. However, in the developing countries, ...

research-article
Snake Venom Database (SVDB): A Potential Resource for Complementary & Alternative Medicine and Drug Designing

Snake venom database (SVDB), an automated customized, subject specific, non-redundant generic data repository built to communicate with and extract all snake venom, toxins and venom components related information from millions of data that can be ...

research-article
Genome-Wide Analysis of the Cytochromes P450 Gene Family in Aspergillus Oryzae

Cytochromes P450 gene family has been shown to play significant roles in various physiological processes of Aspergillus oryzae, including the growth and development, abiotic and biotic stress responses and stress signaling. In this study, the members of ...

SESSION: Bioinformatics and Computational Biology
research-article
Computational Techniques for Analysis of Spatial Time Series on Fish Species Catch Quantity in Greece

This paper is based on a Multidimensional Fishery Time Series Database of Greece that stores spatial, biological, temporal, technical and economic data extracted from National Statistical Service of the country. Time series on fish species catch ...

research-article
Looking at Alzheimer's Disease Using Enhanced Algorithm for Feature Collection

Machine learning technology has taken substantial leaps in the past few years. From the rise of voice recognition as an interface to interact with our computers to self-organizing photo albums and self-driving cars. Neural networks and deep learning ...

research-article
Using Machine Learning Classifiers to Identify the Critical Proteins in Down Syndrome

Pharmacotherapies of intellectual disability (ID) are largely unknown as the abnormalities at the complex molecular level which causes ID are difficult to understand. Down syndrome (DS) which is the prevalent cause of ID and caused by an extra copy of ...

research-article
Estimating Invasion Time in Real Landscapes

Species are threatened by climate changes, unless their populations have the ability to invade landscapes to search for new regions of suitable climate and conditions. It is therefore of utmost importance for ecologists to estimate the invasion time, as ...

research-article
Using the SVM Method for Lung Adenocarcinoma Prognosis Based on Expression Level

Lung cancer is the deadliest cancer in the word, leading to over a quarter of death in the United States in 2017. Gaining precise information on cancer prognosis for patients would greatly benefit their decision making for further treatment plans. While ...

research-article
Noninvasive Prediction of Atrial Fibrillation Recurrence Based on a Deep Learning Algorithm

Atrial fibrillation (AF) is an abnormal heart rhythm. The goal of radiofrequency ablation for AF is to regain a normal heart rhythm. Presently, the commonly used algorithms for prediction of AF recurrence face constraints such as no flexible feature ...

research-article
Deep Neural Network for Classification and Prediction of Oxygen Binding Proteins

The accurate annotation of a protein function is important for understanding life at molecular level. Nowadays, powerful high throughput proteomics technologies provide an unprecedented understanding of the human biology and disease. These technologies ...

research-article
From Biosignals to Affective States: a Semantic Approach

The final goal of Affective Computing is in allowing to recognize human emotional states by means of automatic procedures. Despite scientific literature evidences the concrete usefulness of possible approaches based on biosignals analysis to detect and ...

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