Bioinformatics

Map of the human X chromosome (from the NCBI website). Assembly of the human genome is one of the greatest achievements of bioinformatics. Bioinformatics i/ˌbaɪ.oʊˌɪnfərˈmætɪks/ is an interdisciplinary scientific field that develops methods for storing, retrieving, organizing and analyzing biological data. A major activity in bioinformatics is to develop software tools to generate useful biological knowledge. Bioinformatics is a distinct science from biological computation, the latter being a computer science and computer engineering subfield using bioengineering and biology to build biological computers, whereas bioinformatics simply uses computers to better understand biology. Introduction[edit] History[edit] Sequences. Genomes. Goals[edit] In order to study how normal cellular activities are altered in different disease states, the biological data must be combined to form a comprehensive picture of these activities. Approaches[edit] Major research areas[edit] Sequence analysis[edit]

Machine Learning Machine learning is the science of getting computers to act without being explicitly programmed. In the past decade, machine learning has given us self-driving cars, practical speech recognition, effective web search, and a vastly improved understanding of the human genome. Machine learning is so pervasive today that you probably use it dozens of times a day without knowing it. This course provides a broad introduction to machine learning, datamining, and statistical pattern recognition. Cheminformatics Cheminformatics (also known as chemoinformatics, chemioinformatics and chemical informatics) is the use of computer and informational techniques applied to a range of problems in the field of chemistry. These in silico techniques are used in, for example, pharmaceutical companies in the process of drug discovery. These methods can also be used in chemical and allied industries in various other forms. History[edit] The term chemoinformatics was defined by F.K. Brown [1][2] in 1998: Chemoinformatics is the mixing of those information resources to transform data into information and information into knowledge for the intended purpose of making better decisions faster in the area of drug lead identification and optimization. Basics[edit] Applications[edit] Storage and retrieval[edit] The primary application of cheminformatics is in the storage, indexing and search of information relating to compounds. File formats[edit] Virtual libraries[edit] Virtual screening[edit] See also[edit] References[edit]

mypage I am a PHD (Chemical Informatics ) student at Indiana University Bloomington working with Prof David Wild at the chemgenomics and cheminformatics lab .Our lab is mainly focused on drug discovery and finding relationships between genes and compounds using semantics and data minning approaches Other than that we also work on QSAR , Molecular docking , Machine learning. I am from India I was working with OSDD in cheminformatics making machine learning models for TB drug discovery.I have a lot of experience in Open source tools and like to use them very much for my work. I am also experienced in commercial tools like Pipeline pilot, Ligand scout, Hyperchem, Molegro products. Cheminformatics has lot's to give to pharmaceutical industry . When and where Innovations take place we dont know. High throughput screening Contact Information 2618 Apt G Bloomington Indiana 47408 901 E 10th St. School of informatics and Computing Informatics West Room 205 Email:abseal@indiana.edu abhik1368@gmail.com