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International Conference on Computational Biology and Bioinformatics, will be organized around the theme “Computational Biology: Going into the future one click at a time”

Computational Biology 2018 is comprised of keynote and speakers sessions on latest cutting edge research designed to offer comprehensive global discussions that address current issues in Computational Biology 2018

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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 1-1Functional & comparative genomics
  • Track 1-2Personal genomics
  • Track 1-3Clinical & medical genomics
  • Track 1-4Computational 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 2-1Clinical proteomics
  • Track 2-2Proteome informatics
  • Track 2-3Proteogenomics
  • Track 2-4Protein chip analysis

Clinical Informatics otherwise known as Healthcare Informatics is the application of information technology and informatics to provide healthcare services. Health informatics and bioinformatics comes under biomedical informatics which involves translational bioinformatics which analyzes the relationship between biological and clinical data. Health informatics also called medical informatics, nursing informatics which redefined the health care in designing, implementing and analyzing clinical data Clinical Informatics is concerned with use of information in health care by clinicians. Personalized Medicine assures patient-tailored treatments that upgrade patient care and reduce overall treatment costs by focusing on and “omics” data gathered from patient. Preventive Medicine targets on the health of individuals, groups, and defined populations. Molecular Medicine strives to advocate the understanding of normal body functioning and disease pathogenesis at molecular level. Bioelectronic Medicine is the merging of molecular medicine, neuroscience and bioengineering to develop therapies. Clinical research leads to generation of high-quality, statistically sound and reliable data from clinical trials maintained in Clinical Databases. Bioinformatics tools are profitable in Medical Research helps in the comparison of genetic and genomic data and understanding of various molecules that are amenable for the disease helps to analyze and document the biological systems and pathways. The analytical capability of bioinformatics podium united with clinical data from patient in Electronic Medical Reports can affirm potential biomarkers and clinical phenotypes that allow researchers to develop experimental strategies using selected patient.

  • Track 3-1Electronic medical reports
  • Track 3-2Personalized medicine
  • Track 3-3Preventive medicine

Computational biology is similar to bionformatics, where computers are used to store and process biological data, rather using computer engineering and bioengineering to build computers. Computation genomics is a sub field of science Computational biology which is related to the study of genomes of cells and organisms. It encompasses a major part in Bioinformatics. This field is still under development and has several untouched projects like analysis of intergenic regions.

  • Track 4-1Human Genome Project
  • Track 4-2Contribution of Computation Genomics research to biology
  • Track 4-3Cancer Genomics
  • Track 4-4Topological Data Analysis

Evolutionary Bioinformatics is an advanced discipline that addresses the practice of data processing and the engineering of data for the investigation of biological evolution. Amassing of information at the huge scale has turned out to be progressively cost-efficient through latest advances in high-throughput genotyping and sequencing innovations. It sees genomes as medium for conveying different types of data through the generations from the past to present. The study of evolutionary biology uncovers that living beings of different types which were previously oblivious originated over the span of numerous eras mostly through moderate and progressive alterations.

  • Track 5-1Comparative genomics
  • Track 5-2Phylogenetics
  • Track 5-3Evolution, taxonomy and systematics
  • Track 5-4Population genetics

Computational pharmacology is a sub field of computational biology where the effects of genomic data is studied inorder to find links between genotypes amd diseases and then screening of drug data. There are numerous data sets available and researchers and scientists are developing computational methods to analyze these data sets. This inturn helps for the development of accurate drugs. Predicting, modeling and simulating potential theraputic agents against the target is the first step of success in drug discovery process. Computational pharmacology tries to bridge the gap between strcture and function via dynamics.

  • Track 6-1Computational approaches to drug discovery

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 modeling. In more recent advances, the equivalent of an industrial revolution for ontology was pronounced by the apparition of latest technologies representing bio-ontologies.

  • Track 7-1Web services in bioinformatics
  • Track 7-2Bioinformatics tools & software
  • Track 7-3Biological databases

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 8-1Computational statistics
  • Track 8-2Bayesian methods
  • Track 8-3Statistical genetics
  • Track 8-4Medical statistics and informatics

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 modeling 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 9-1Computational epigenetics
  • Track 9-2Applications of epigenetics in cancer
  • Track 9-3Epigenome prediction
  • Track 9-4Gene Silencing

Clinical case reports are compelling source of evidence in the field of medicine and is aimed to improve global health and concise about a common or critical clinical scenario and develop a broader search for evidence. Case reports provide detailed information of the symptoms, diagnosis, signs, treatment, and effect of an individual patient. It contains a demographic report of the patient, but usually portrays an unusual or new instance. A favourable case report gives a clear perception about the gravity of the observation being reported. Case report aids in the identification of advanced trends or diseases and discover new drug, its side effects and potential usage. It even analyzes limited manifestations of a disease. Case reports play a significant role in medical discipline thereby administering a structure for case-based training.

  • Track 10-1Alzheimer case reports
  • Track 10-2Cancer case reports
  • Track 10-3Cystic fibrosis case reports

Bioinformatics and computational biology are interrelated disciplines allowing computational methods to analyse biological data and develop algorithms and analytical methods by acquiring knowledge from various disciplines like computer science, physics, statistics etc. This field is gaining importance in various research fields like Neural Networks, Artificial Intelligence for developing algorithms. It is used in developing bioinformatics software and tools for drug designing, molecular simulations, drug discovery, molecular modeling and numerous biological databases. Subfields related to this topic are computational immunology, computational pharmacology, computational neuroscience, computational cancer biology etc.

  • Track 11-1Data mining and Machine Learning
  • Track 11-2Artificial Intelligence
  • Track 11-3Neural Networks
  • Track 11-4Visual Analytics

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 modeling 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 12-1Cancer systems biology
  • Track 12-2Systems theory for complex dynamical systems
  • Track 12-3Transcriptomics
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 13-1RNA structure and function
  • Track 13-2Protein structure analysis
  • Track 13-3Protein structure and function prediction

Immunology involves the development and application of methods of bioinformatics, mathematics and statistics for the study of immune system biology. Through drug discovery mechanism new drugs can be discovered and designed and the causes of the diseases can be analyzed and ways could be found to tackle them. The modern drug discovery process integrates the understanding of the molecular basis for a disease with crucial understanding of how potential drug molecules interact with particular disease targets and the whole organism. Bioinformatics is a growing field which can explore the causes of diseases at the molecular level, explain the occurrence of the diseases from the genetic angle and make use of computer techniques to diminish the scope of study and enhance the efficiency of the results so as to curtail the cost and time.

  • Track 14-1Innovative methods and techniques in immunology
  • Track 14-2Immune cells & proteins
  • Track 14-3Clinical biomarkers