Call for Abstract

7th International Conference on Biostatistics and Bioinformatics, will be organized around the theme “Exploring Advances in Biostatistics & Bioinformatics”

Biostatistics 2018 is comprised of 15 tracks and 96 sessions designed to offer comprehensive sessions that address current issues in Biostatistics 2018.

Submit your abstract to any of the mentioned tracks. All related abstracts are accepted.

Register now for the conference by choosing an appropriate package suitable to you.

It encompasses the statistical strategies which are accustomed to govern uncertainties in the field of medicine and health. It comprehends biostatistics in clinical research and clinical trials, biostatistics research and methodology, clinical decision making, statistical methods in diagnostic drugs , statistical and computing methods

  • Track 1-1Biostatistics in Clinical research
  • Track 1-2Biostatistics research and methodology
  • Track 1-3Clinical decision making
  • Track 1-4Statistical methods in diagnostic medicine
  • Track 1-5Basic Statistics of Biomarkers and Clinical Trials
  • Track 1-6Biomedical Statistics

It includes strategies which are utilized as a part of biostatistics and computing. It incorporates points such as vigorous techniques in biostatistics, longitudinal studies, analysis with deficient data, meta-analysis, Monte-Carlo strategies, quantitative issues in health-risk analysis, statistical methodologies in genetic studies, ecological statistics and biostatistical routines in epidemiology.

  • Track 2-1Longitudinal studies
  • Track 2-2Analysis with incomplete data
  • Track 2-3Meta-Analysis
  • Track 2-4Quantitative problems in health-risk analysis
  • Track 2-5Biostatistical methods in epidemiology

It is a subset of the sphere of statistics during which the proof about the concerning verity of the world is expressed in terms of degrees of belief or, ma lot specifically, Bayesian probabilities. It includes of varies approaches like Bayesian inference, stochastic structural improvement and Bayesian statistics, semi-parametric Bayesian analysis, Bayesian multiple modification point analysis, infrared spectroscopic analysis with Bayesian statistics and Bayesian dynamic models

  • Track 3-1Stochastic structural optimization and bayesian statistics
  • Track 3-2Semi parametric bayesian analysis
  • Track 3-3Bayesian multiple change point analysis
  • Track 3-4Infrared spectroscopy with bayesian statistics
  • Track 3-5Bayesian dynamic models

It is the study of science that deals with the statistical methods for describing and comparing the phenomenon of particular subject which helps in managing medical uncertainties. Its applications are wide spread in medicine, health, biology etc. for interpretation of data based on observations and facts.

  • Track 4-1Biostatistics in pharmacy
  • Track 4-2Biostatistics in medical
  • Track 4-3Biostatistics in healthcare
  • Track 4-4Biostatistics in genetics
  • Track 4-5Ecological statistics

In statistics study, regression analysis has been statistical process for estimating the relationships among variables. It includes several techniques for modelling and analysing many variables, once the main focus is on the link between a dependent variable and one or a lot of freelance variables. This track contains numerous sub topics like linear and non-linear analysis, variance and regression analysis, statistical methods for categorical data analysis, multiple regression with categorical information and biostatistical analysis software.

  • Track 5-1Linear and non-linear analysis
  • Track 5-2Analysis of variance and regression
  • Track 5-3Multiple regression with categorical data
  • Track 5-4Robust methods in biostatistics
  • Track 5-5Biostatistical analysis softwares

It incorporates the different civilized systems utilized as a part of the biostatistical data analysis. Different subjects which are being incorporated are data sets, hierarchical models, causal inference, nonparametric alongside the statistical genetics, Mantel–Haenszel test and the biometric ramifications of these data analysis methods

  • Track 6-1Large data sets
  • Track 6-2Hierarchical models
  • Track 6-3Nonparametrics
  • Track 6-4Mantel–Haenszel test
  • Track 6-5Biometric implications
  • Track 6-6Causal inference

Structural bioinformatics is a sub discipline of bioinformatics that deals with the three dimensional structures of biomolecules. This field portrays the goals to create methods for manipulating information about biological macromolecules and the application of these methods to solve problems in biology and creating new knowledge. It attempts to model and discover the basic principles underlying biological machinery at the molecular level. Structural bioinformatics combines applications of physical and chemical principles with algorithms from computational science. With the success of the genome sequencing projects, the evolution of high-throughput methods for expression analysis and compound identification, structural bioinformatics is now resurgent and is doing its part to accelerate the drug discovery process. The techniques that structural bioinformatics involves are particularly valuable in the area from target identification to lead discovery. Structural bioinformatics can be used for function and ligand prediction in the case of novel targets.

  • Track 7-1RNA structure and function
  • Track 7-2Protein structure analysis
  • Track 7-3Protein structure and function prediction

Systems biology includes the study of systems of biological components, which may be molecules, cells, organisms or entire species. Systems Biology deals with data and models at many different scales, from individual molecules through to whole organisms. Computational systems biology addresses questions fundamental to our understanding of life and progress here will lead to practical innovations in medicine, drug discovery and engineering. It aims to develop and use efficient algorithms, data structures, visualization and communication tools with the goal of computer modelling of biological systems. Systems Biology approach harnesses the power of computation and systems-level analyses to formulate and solve critical biological problems. This integrative approach of systems biology will close the loop from individual genetics to populations, and constitute the strongest asset for the successful translation of systems biology findings to clinical applications.

  • Track 8-1Cancer systems biology
  • Track 8-2Systems theory for complex dynamical systems
  • Track 8-3Machine learning algorithm

Biostatistics is a branch of applied statistics and deals with developing and applying techniques to summarize and evaluate medical and biological data. The field of biostatistics to bioinformatics furnish quantitative answers to complicated questions from complicated data. The dominant objective of this conference is to conceive a medium for statisticians from across the world to present their latest study, discovery in statistical applications which can prompt novel research projects and directions as well as improve statistical programs. Specialized and technical methods have been made and are currently advancing in the fields of biostatistics and bioinformatics as a mutual resource to exhibit them with a wide range of favourable applications in genetics, genomics, and biomedical areas. The doctrine of biostatistics and bioinformatics will be popularized through driving applications which offers learning approach and therefore, is available to a wide range of fields.

  • Track 9-1Computational Statistics
  • Track 9-2Bayesian Methods
  • Track 9-3Statistical Genetics
  • Track 9-4Medical Statistics and Informatics

Practically about 600 bioinformatics tools were advanced over the past two years, and are being used to facilitate data analysis and its interpretation. Web assistance in bioinformatics provides interfaces that have been developed for an ample array of applications for bioinformatics. The main enhancement derived from the fact that end users do not have to deal with software and database preservation overheads. There are differing software predominant for bioinformatics like open-source, sequence alignment, healthcare, freeware molecular graphics systems, biomedical and molecular mechanics modelling. In more recent advances, the equivalent of an industrial revolution for ontology was pronounced by the apparition of latest technologies representing bio-ontologies.

  • Track 10-1Web services in bioinformatics
  • Track 10-2Bioinformatics Tools & Software
  • Track 10-3Biological databases

Biometric security: It incorporates different biometric devices and calculations which are utilized to execute security in today's universe of innovation. Biometrics security incorporates different points like Personal identity verification, Human activity acknowledgment, Legal similarity for biometric systems, Crime counteractive action,, Biometric devices and calculations, Behavioral intelligence, Biometric arrangements, biometric security authentication and multi touch displays in biometrics.

  • Track 11-1Personal identity verification
  • Track 11-2Human activity recognition
  • Track 11-3Legal compatibility for biometric systems
  • Track 11-4Crime prevention
  • Track 11-5Biometric devices and algorithm
  • Track 11-6Behavioral intelligence
  • Track 11-7Multi touch displays in biometrics
  • Track 11-8Advances in biometric security systems
  • Track 11-9Palm print identification and fingerprinting
  • Track 11-10Biometric solutions
  • Track 11-11Biometric security authentication

Statistical genetics is a scientific field concerned with the development of statistical methods for drawing inferences from genetic data. The term is most commonly used in the context of human genetics

  • Track 12-1Genetics and quantitative Genetics
  • Track 12-2Phylogenetic analysis
  • Track 12-3Principal component analysis in Genetics
  • Track 12-4Linear mixed models (LMM) in Genetics
  • Track 12-5Mutation models

Genomics includes the study of genomes, particularly the set of techniques, analytical methods, and scientific questions related to the study of complete genomes. Scientists have progressed from the analysis of a small number of genes to the analysis of thousands of genes, from the study of the units of inheritance to the whole genome of an organism. Genomics straps the availability of complete DNA sequences for entire organisms by the latest next-generation sequencing technology. Next-generation sequencing has led to spectacular improvements in the speed, capacity and affordability of genome sequencing. Genome sequencing is expected to have the most impact in characterizing and diagnosing genetic diseases; for appropriate treatment; and providing information about an individual’s likely response to treatment to reduce adverse drug reactions. Genomics and bioinformatics are now poised to revolutionize the healthcare system by developing customized and personalized medicine

  • Track 13-1Functional & comparative genomics
  • Track 13-2Personal genomics
  • Track 13-3Clinical & medical genomics
  • Track 13-4Computational genomics

Proteomics is a branch of molecular biology that is concerned with the systematic, high-throughput approach to protein expression investigation of an organism or a cell. It is a large-scale comprehensive study of a specific proteome, including information on protein affluence, their variations and alterations, along with their interacting partners and networks, in order to discern cellular processes. Proteomics enables the understanding the structure, function and interactions of the entire protein content in a specific organism. Bioinformatics for proteomics has grown significantly in the recent years. The ability to process a high amount of data together with high specificity and precision of the new algorithm in the protein description, characterization and quantization makes it possible to obtain a high amount of elaborated data. Bioinformatics tools for proteomics have diverse applications ranging from simple tools to compare protein amino acid compositions to refined software for massive protein structure determination.

  • Track 14-1Clinical proteomics
  • Track 14-2Proteome informatics
  • Track 14-3Proteogenomics
  • Track 14-4Protein chip analysis

Epigenetics is a study of effect on gene activity and expression by chromosomal changes and also heritable phenotypic change that doesn’t come from modification of a genome. Computational Epigenetics which uses data from bioinformatics datasets for analysis and modelling of DNA. Research areas including epigenetic data processing and analysis , epigenome prediction uses large amounts of data for data processing  to predict the epigenetic information from genomic sequence utilising tools and software of bioinformatics. Research topics originating from this field are Population Epigenetics, Evolutionary Epigenetics, Genome Browsers and Medical Epigenetics

  • Track 15-1Computational epigenetics
  • Track 15-2Applications of epigenetics in cancer
  • Track 15-3Epigenome prediction
  • Track 15-44Gene Silencing