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2nd International Conference on Computational Biology and Bioinformatics, will be organized around the theme “Exploring the Challenges and Excellence in Computational Biology Research”

Computational Biology 2019 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 2019

Submit your abstract to any of the mentioned tracks.

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Computational biology and Bioinformatics   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, data mining, machine learning and Artificial Intelligence for developing algorithms. It is used in developing bioinformatics software and tools for drug designing, molecular simulations, drug discovery, molecular modeling and several biological databases. Subfields related to this topic are computational immunology, computational pharmacology, computational neuroscience, computational cancer biology, Computational chemistry and Chemical biology etc. 

  • Track 1-1Data mining and Machine Learning
  • Track 1-2Computational anatomy
  • Track 1-3Artificial Intelligence
  • Track 1-4Computational biomodeling

Computational genomics refers to the use of computational and statistical analysis to decipher biology from genome sequences and related data, including both DNA and RNA sequence as well as other "post-genomic" data. These, in combination with computational and statistical approaches to understanding the function of the genes and statistical association analysis, this field is also often referred to as Computational and Statistical Genetics/genomics. As such, computational genomics may be regarded as a subset of bioinformatics and computational biology, but with a focus on using whole genomes to understand the principles of how the DNA of a species manages its biology at the molecular level and beyond.

  • Track 2-1Human Genome Project
  • Track 2-2genome sequences
  • Track 2-3Cancer Genomics
  • Track 2-4 Bio-sequence analysis

Computational neuroscience is a branch of neuroscience which employs mathematical models, theoretical analysis and abstractions of the brain to understand the principles that govern the development, structure and cognitive abilities of the nervous system. Computational neuroscience focuses on the description of biologically plausible neurons and their physiology and dynamics, and it is therefore not concerned with biologically unrealistic disciplines such as connectionism, machine learning, neural networks, artificial intelligence and computational learning theory.

  • Track 3-1Single-neuron modeling
  • Track 3-2Sensory processing
  • Track 3-3Computational clinical neuroscience

Computational chemistry is a branch of chemistry that uses computer simulation to aid in solving chemical problems. Computational chemistry uses methods of theoretical chemistry, incorporated into efficient computer programs, to calculate the structures and properties of molecules and solids. It is also used to study the fundamental properties of atoms, molecules, and chemical reactions, using quantum mechanics and thermodynamics. Chemical Biology research practices the tools of chemistry and synthesis to understand biology and disease pathways at the molecular level. Advanced biological chemistry interests include various topics such as nucleic acids, DNA repair, bioconjugate chemistry, electron transport, peptides and peptidomimetics, glycoscience, biochemical energy, vitamins, coenzymes, biomolecular structure and function, drug activity, imaging, and biological catalysis.

  • Track 4-1Molecular mechanics and Molecular Sensing
  • Track 4-2Chemical methods to stem-cell biology
  • Track 4-3Bio organic and inorganic Chemistry

Next generation sequencing (NGS), is any of several high-throughput approaches to DNA sequencing using the concept of massively parallel processing; it is also called Massive parallel sequencing. Next generation sequencing is an Application of genetic sequencing which is used to identify the populations at high risk or target therapies to patients those who are likely to respond. The Next generation sequencing (NGS) market assessment was made based on products, technologies, end users, applications and geography.

  • Track 5-1Illumina (Solexa) sequencing
  • Track 5-2Roche 454 sequencing
  • Track 5-3Ion torrent: Proton / PGM sequencing
  • Track 5-4SOLiD sequencing

Metabolomics refers to the systematic identification and quantification of the small molecule metabolic products of a biological system (cell, tissue, organ, biological fluid, or organism) at a specific point in time. Mass spectrometry and NMR spectroscopy are the two techniques most often used for metabolome profiling.Systems biology refers to the computational and mathematical modeling of complex biological systems. It is a biology-based interdisciplinary field of study that focuses on complex interactions within biological systems, using a holistic approach to biological research.

  • Track 6-1Metabolites
  • Track 6-2Exometabolomics
  • Track 6-3Metabolome
  • Track 6-4Cancer systems biology
  • Track 6-5Systems theory for complex dynamical systems
  • Track 6-6Transcriptomics

Molecular biology is a branch of biology that concerns the molecular basis of biological activity between biomolecules in the different systems of a cell, including the interactions between DNA, RNA, proteins and their biosynthesis.Structural biology refers to the study of molecular structure and dynamics of biological macro-molecules like proteins and nucleic acids, and how changes in their structures affect their function. Structural biology is a branch of molecular biology, biochemistry, and biophysics anxious with the molecular structure of biological macromolecule.

  • Track 7-1Molecular cloning
  • Track 7-2Polymerase chain reaction
  • Track 7-3Microarrays
  • Track 7-43D Structure Determination
  • Track 7-5Structural Biology Databases
  • Track 7-6Structural Biology in Cancer Research

Genetics refers to the study of genes, genetic variation, and heredity in living organisms. It is mainly considered a field of biology but intersects frequently with many other life sciences and is strongly linked with the study of information systems.Epigenetics refers to the 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.

  • Track 8-1Molecular genetics
  • Track 8-2Human Genetics
  • Track 8-3Medical Genetics
  • Track 8-4Genetic Disorders
  • Track 8-5Computational epigenetics
  • Track 8-6Applications of epigenetics in cancer

Computational pharmacology is a sub branch of computational biology where the effects of genomic data is studied inorder to find links between genotypes and diseases and then screening of drug data. There are several data sets available and researchers and scientists are developing computational methods to analyze these data sets. Computational pharmacology tries to bridge the gap between strcture and function via dynamics.

  • Track 9-1 Computational approaches to drug discovery

Immunology is a branch of biology which covers the study of immune systems in all organisms. It involves the development and application of methods of bioinformatics, mathematics and statistics for the study of immune system biology.Drug discovery is the process through which potential new drugs are identified. Drug discovery involves a wide range of scientific disciplines, including biology, chemistry and pharmacology. The advanced drug discovery process integrates the understanding of the molecular basis for a disease with crucial understanding of how potential drug molecules interact with disease targets and the whole organism.

  • Track 10-1Innovative methods and techniques in immunology
  • Track 10-2Immune cells & proteins
  • Track 10-3Clinical biomarkers
  • Track 10-4Advancing Drug Discovery

Biostatistics is a field of applied statistics and deals with developing and applying techniques to summarize and evaluate medical and biological data. The branch of biostatistics to bioinformatics furnish quantitative answers to complicated questions from complicated data. The 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.

  • Track 11-1Computational statistics
  • Track 11-2Bayesian methods
  • Track 11-3Statistical genetics
  • Track 11-4Medical statistics and informatics

Structural bioinformatics is the branch of bioinformatics that deals with the three-dimensional structure of biological macromolecules such as proteins, RNA, and DNA. Structural bioinformatics deals with generalizations about macromolecular 3D structure such as comparisons of overall folds and local motifs, principles of molecular folding, evolution, and binding interactions, and structure/function relationships. Evolutionary Bioinformatics is an advanced field that addresses the practice of data processing and the engineering of data for the investigation of biological evolution.

  • Track 12-1Protein structure analysis
  • Track 12-2Protein structure and function prediction
  • Track 12-3Comparative genomics
  • Track 12-4Evolution, taxonomy and systematics
  • Track 12-5Population genetics

Biodiversity Informatics is the application of informatics techniques to biodiversity information for improved management, presentation, discovery, exploration, analysis. Biodiversity Informatics typically builds on a foundation of taxonomic, biogeographic, or ecological information stored in digital form, which, with the application of modern computer techniques, can yield new ways to view and analyse existing information. Biodiversity informatics is a relatively young discipline but has hundreds of practitioners worldwide, including the numerous individuals involved with the design and construction of taxonomic databases. The word "Biodiversity Informatics" is generally used in the broad sense to apply to computerized handling of any biodiversity information; the somewhat broader term "bioinformatics" is often used synonymously with the computerized handling of data in the specialized area of molecular biology.

  • Track 13-1Biodiversity
  • Track 13-2New Approaches to Biodiversity Infrastructure
  • Track 13-3Ecological Informatics & Modelling

Biomedical and health informatics applies fundamental of computer and information science to the advancement of life sciences research, health professions education, public health, and patient care. This multidisciplinary and integrative branch focuses on health information technologies (HIT), and involves the computer, cognitive, and social sciences. Informatics is the science of how to use data, information and knowledge to improve human health and the delivery of health care services.

  • Track 14-1Biomarkers
  • Track 14-2Biomedicine
  • Track 14-3Medical Informatics
  • Track 14-4Sensor 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 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 15-1 Web services in bioinformatics
  • Track 15-2Bioinformatics tools & software
  • Track 15-3Biological databases

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 16-1Alzheimer case reports
  • Track 16-2Cancer case reports
  • Track 16-3Cystic fibrosis case reports