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Identification and Characterization of Strain Specific Drug Target by Subtractive Genome Analysis of Methicillin Resistance Staphylococcus aureus
Kiran Saeed and Reaz Uddin

This study aimed to identify and characterize strain specific essential protein targets, which will eventually help in the identification of druggable proteins in two strains of MRSA by using different Bioinformatic tools and databases. We adopting a subtractive genome approach within the domain of Computational Biology.

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Reaxys Xcelerate – Less Searching. More Discovery
Keshav Dutt Sharma

Reaxys Xcelerate is a new premium version of Reaxys. Reaxys is a web based workflow tool for synthetic chemists. It is designed to support the optimization of synthetic processes and offers a valuable resource for accurate & validated experimental reaction & substance data.

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Processing and Managing Analytical Data to Extract and Share Knowledge – How Far We’ve Come and Why It’s So Hard?
Michael Boruta and Sanjivanjit K. Bhal, Advanced Chemistry Development, Inc.

This paper discusses the ACD/Spectrus Processor, the new all-in-one analytical data processing and chemical characterization software.

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GALAS Modeling Methodology Applications In The Prediction Of Drug Metabolism Related Properties
Remigijus Didziapetris, Justas Dapkunas, Andrius Sazonovas and Pranas Japertas

Analytical identification of metabolites for a drug candidate is usually a time consuming and low-throughput task and is performed only at the later phases of drug development. Therefore the possibility to predict possible sites of human liver microsomal (HLM) metabolism using in silico techniques would be a very attractive feature for any medicinal chemist.

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Effective Use of In-Silico Tools in Lead Optimization
Pranas Japertas, Andrius Sazonovas and Kiril Lanevskij

Of all the challenges facing medicinal chemists in general, one of the most significant must be transforming an active molecule into a viable drug. Lead optimization efforts are guided by a combination of factors, such as potency, ease of synthesis, patentability concerns, specific synthetic constrains of the interaction with the target, as well as the lead’s toxicity and ADME properties.

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New Approach for In Silico Genotoxicity Testing of Impurities and Degradants
Kiril Lanevskij, Liutauras Juska, Remigijus Didziapetris and Pranas Japertas

This study presents a novel approach to aid this assessment based on probabilistic predictors of mutagenicity in Ames test and binding to Estrogen Receptor, supplemented by a knowledge-based system of structural alerts.

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QSAR Model of Regioselectivity of Metabolism in Human Liver Microsomes: Development, Validation, Comparison and Adaptation to Novel Compounds
Justas Dapkunas, Andrius Sazonovas and Pranas Japertas

Analytical identification of metabolites for a drug candidate is usually a time consuming and low-throughput task which is performed only in late drug development phases. Therefore the ability to predict possible sites of human liver microsomal metabolism using in silico techniques would be highly beneficial for any medicinal chemist.

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In silico Identification of Metabolic Soft Spots: Case Study Using ACD/ADME Suite Software
Justas Dapkunas, Andrius Sazonovas, Remigijus Didziapetris and Pranas Japertas

Metabolic stability, determined in liver microsomes, is one of the primary assays used in early drug discovery. A key factor limiting compound half-life is the cytochrome P450 mediated metabolism. High clearance by these enzymes implies a higher and more frequent dosing as well as poses a risk for individual variations in exposure.

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Analytical and Chemical Knowledge Management Software for Drug Metabolism Science
Graham A. McGibbon, Karim Kassam, and Susan Ling

Characterizing metabolite structures and metabolic pathways is essential to understanding the potential biological implications of compounds in drug discovery.

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Showing Results 31 - 40 of 80
Scientific News
Personalised Medicine: Dose by Design
Personalised medicine holds the promise of a new approach to healthcare, tailored exactly to our individual needs, as Congenica's Nick Lench discussed on a recent BBC Radio 4 programme.
Expanding Knowledge of Viral Diversity
Environmental datasets help researchers double the number of microbial phyla known to be infected by viruses.
Computers Better Predict Lung Cancer Type, Severity
Study shows automating the analysis of cancer tissue samples increases the accuracy of tumor classification and patient prognoses.
Using Big Data to Discover Potential Cancer Biomarkers
University of Hawai'i Cancer Center researchers used "Big Data" to discover potential cancer biomarkers, a panel of six long intergenic non-coding RNAs (lincRNAs), for the diagnosis of all types of cancers including lung, breast, prostate, liver and ovarian cancers.
Protecting Privacy in Genomic Databases
System helps ensure databases used in medical research will not leak patients’ personal information.
Algorithm To Find Precise Cancer Treatments For Patients Developed
The JAMMIT algorithm could help predict which patients will benefit most from chemotherapy.
Depression Genetics Insight from Crowd-Sourced Data
Genome sites liked to depression have been discovered from data shared by people who had purchased their genetic profiles online.
Detecting Hazardous Chemicals in Complex Mixtures
Researchers are pioneering a new chemical substance analyis software technique that could increase illicit substance detection.
Researchers Develop Software That Could Facilitate Drug Development
AptaTRACE can identify aptamers, potentially speed drug advancement.
Protein Nanocages Could Improve Drug Design and Delivery
HHMI scientists have designed and built 10 large protein icosahedra that are similar to viral capsids that carry viral DNA.
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