Pharma companies in india

Click the following URL and you can get the list of the pharmacutical companies:

http://www.naukri2000.com/careers/pharmaceutical.php3

BIOINFORMATICS AND BIO TECH COMPANIES

BIOINFORMATICS COMPANIES:
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BIO TECH COMPANIES:
· www.5prime.com
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4PEAKS

Overview
4Peaks is a program that helps molecular biologists to visualize and edit their DNA sequence files. At last there is a decent solution for analyzing trace files on the MacOSX platform, taking another step away from slow and non-native programs from the MacOS9 period. Also, 4Peaks supports most commonly used sequence file formats right out of the box, you no longer have to convert them first using AppleScripts or other painstaking methods. Analyzing your sequence was never so much fun! Download >>

Key Features

Move mouse over buttons to learn more...
For Peaks - 4Peaks can read and write most common trace file formats, and allows direct access to both sequence and translation. It offers the ability to analyze, edit and correct your sequence data. 4Peaks leverages MacOSX strong foundation to bring you the best sequence trace viewer available. period.
New Features in 4Peaks 1.7

The latest version of 4Peaks is now fully compliant with MacOSX 10.4 Tiger. In addition, it now runs natively on Intel-based Macs. Finally, we continued fixing a number of reported bugs.

Gene structure Prediction tool

TIGR-Glimmer: Glimmer are for identification of possible genes for prokaryotes sequences . It is based on interpolated Markov models to identify the coding regions and distinguish them from noncoding DNA.Download Glimmer Via FTP
TIGR-GlimmerM: A gene finder derived from Glimmer, but developed specifically for eukaryotes. It is based on a dynamic programing algorithm that considers all combinations of possible exons for inclusion in a gene model and chooses the best of these combinations. Download Glimmer Via FTP
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Alignment and Similarity searching tools

EBI- Fasta executable: Provides sequence similarity searching against nucleotide and protein databases using the Fasta programs. Fasta can be very specific when identifying long regions of low similarity especially for highly diverged sequences.Download EBI-Fasta executable via FTP
EBI-Clustal W is a general purpose multiple sequence alignment program for DNA or proteins.It produces biologically meaningful multiple sequence alignments of divergent sequences. It calculates the best match for the selected sequences, and lines them up so that the identities, similarities and differences can be seen.Download EBI-Clustal W via FTP
Clustal X: Clustal X is a new windows interface for the ClustalW multiple sequence alignment program. It provides an integrated environment for performing multiple sequence and profile alignments and analysing the results. The sequence alignment is displayed in a window on the screen. A versatile coloring scheme has been incorporated allowing you to highlight conserved features in the alignment. The pull-down menus at the top of the window allow you to select all the options required for traditional multiple sequence and profile alignment. Download Clustax (Windows OS)
TIGR-MUMmer(fast alignment of large-scale DNA and protein sequences):A system for aligning whole genome sequences. Using an efficient data structure called a suffix tree, the system is able rapidly to align sequences containing millions of nucleotides. Download MUMer Via FTP
TIGR-AAT package(A tool for analyzing and annotating genomic sequences): The AAT package includes two sets of programs, one set (DPS/NAP) for comparing the query sequence with a protein database, and the other (DDS/GAP2) for comparing the query with a cDNA database (Huang et al., 1997).Download AAT package via FTP

Binding Affinity Prediction of Protein-Ligand Server(BAPPL)

BAPPL server
HIV-I Protease complexed with U75875 (1hiv.pdb)
Welcome to the BAPPL server
Binding Affinity Prediction of Protein-Ligand (BAPPL) server computes the binding free energy of a non-metallo protein-ligand complex using an all atom energy based empirical scoring function [1] & [2].
BAPPL server provides two methods as options:Method 1 : Input should be an energy minimized protein-ligand complex with hydrogens added, protonation states, partial atomic charges and van der Waals parameters (R* and ε) assigned for each atom. The server directly computes the binding affinity of the complex using the assigned parameters. For format specifications on the input, please refer to the README file.Method 2 : Input should be an energy minimized protein-ligand complex with hydrogens added and protonation states assigned. The net charge on the ligand should be specified. The server derives the partial atomic charges of the ligand using the AM1-BCC procedure [3] and GAFF [5] force field for van der Waals parameters. Cornell et al. force field [4] is used to assign partial atomic charges and van der Waals parameters for the proteins. For format specifications on the input, please refer to the README file.
For the purpose of validation of the empirical scoring function [1] a dataset of 161 non-metallo protein-ligand complexes has been prepared. Click here to access the Protein-Ligand Complex Dataset.
BAPPL server
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E-Mail
E-mail address



E-Mail
E-mail address


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Select Option
Method 1 Method 2 Net Ligand Charge 0 -10 -9 -8 -7 -6 -5 -4 -3 -2 -1 0 +1 +2 +3 +4 +5 +6 +7 +8 +9 +10
Input PDB file E-mail address
Upload
Input PDB file







-->
Instructions for using the server
The input protein-ligand complex should follow the format described in the README files. In case of any differences, either an error is generated resulting in the termination of computation or the predicted binding affinity value will have errors in it.
Please specify the E-mail address, Name and Institution.
Choose either one of the options : "Method 1" OR "Method 2"
For Method 2, specify the Net ligand charge.
Browse and select the input file.(The input file name should not contain whitespace(s) & PDBID should be a four letter code, like 1a30.pdb)
Click Submit to get the result.
The Predicted Binding Affinity value will be sent via E-mail at the address specified. The computation may take 5-10 minutes depending upon the load on the web server and the number of atoms in the input file.
IMPORTANT: The predicted binding affinities are dependent upon:
The protonation states assigned to the ligand and protein atoms.
The procedure used to derive the partial atomic charges for ligand atoms like (AM1-BCC, HF/6-31G*/RESP, etc.) and the force field used to assign the partial atomic charges for the protein atoms like (AMBER, CHARMM, OPLS, etc.).
The force field used to assign the van der Waals parameters for ligand and protein atoms.
Energy minimization / geometry optimization protocol used to remove any clashes from the complex.
NOTE : The empirical scoring function [1] has been calibrated using the HF/6-31G*/RESP equivalent partial atomic charges and Cornell et al. [4] and GAFF [5] force field parameters for proteins and ligands respectively. We have provided the AM1-BCC procedure for deriving partial atomic charges of ligands for Method 2 because this procedure is fast and produces charges of comparable accuracy to the HF/6-31G*/RESP method.
REFERENCES
[1] Jain, T. and Jayaram, B. (2005) An all atom energy based computational protocol for predicting binding affinities of protein-ligand complexes. FEBS Letters, 579, 6659-6666. [Abstract]
[2] Arora, N. and Jayaram, B. (1998) Energetic of base pairs in B-DNA in solution: An appraisal of potential functions and dielectric treatments. J. Phys. Chem. B. 102, 6139-6144. [Abstract]
[3] Jakalian, A., Bush, B.L., Jack, D.B. and Bayaly, C.I. (2000) Fast, efficient generation of high-quality atomic charges. J. Comput. Chem. 21, 132-146.
[4] Cornell, W.D. et al. (1995) A second generation force field for the simulation of proteins, nucleic acids and organic molecules. J. Am. Chem. Soc. 117, 5179-5197.
[5] Wang, J., Wolf, R.M., Caldwell, J.W., Kollman, P.A. and Case, D.A. (2004) Development and testing of a general amber force field. J. Comput. Chem. 25, 1157-1174.

SOFTGENETICS

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GeneMarker® for Multiplex Ligation-dependent Probe Amplification (MLPA*)
GeneMarker now has the capability to analyze data from Multiplex Ligation-dependent Probe Amplification (MLPA). Click here for more information on MLPA tests and test kits.
Current applications include the detection of exon deletions in the human BRCA1, MSH2 and MLH1 genes associated with breast cancer and colon cancer, detection of trisomies as in Down Syndrome (47, XX + 21), categorization of chromosomal abnormalities in cell lines and tumor samples, and mutation detection.
With GeneMarker, MLPA data analysis is an efficient, quick, and easy process, with features such as customized reporting, intensity comparison, data normalization, and printing.
GeneMarker is an excellent tool for nearly all Genotyping applications. The exclusive, high resolution gel image provides a quick overview of the MLPA analysis, allowing rapid discernment of areas of interest. The MLPA analysis accurately identifies exon deletions and duplications through calculating the intensity ratios of sample to control.
MLPA Normalization
GeneMarker can normalize MLPA derived data by an internal control probe method or an inter-lane population method. The user is able to specify the normalization method in the Run Wizard prior to analysis. The normalization is similar to that designed by Graham R. Taylor at St. James’s University Hospital, Leeds. You may find a detailed description of the method titled “Regression-enhanced examination of MLPA (REX-MLPA): towards automated and objective scoring” at http://leedsdna.info/science/dosage/REX-MLPA/REX-MLPA_CMGS04.ppt.
The internal control probe method normalizes the data by comparing the individual peak intensities within one sample lane. The inter-lane population method compares the peak intensities of the amplified probes between sample lanes. Both normalization methods take the square root of the intensity ratio and plot the ratios to model a linear regression, using the control probes as reference points.
MLPA Report
MLPA Intensity Report
GeneMarker is designed to identify copy number changes in genomic sequences. The main interface window after running the data is shown above. The various peaks in the electopherogram represent different amplified probes within the sample and can be labeled accordingly in the Panel Editor. The report displays the presence and absence of the amplified probes within each sample. The green flag is used to represent high quality peaks, whereas a yellow symbol is used to represent peaks with a lower score. This report may be saved as a text file for printing in Excel.
The user may also display the intensity for the peaks representing the amplified probes. Since MLPA is designed to locate exonic duplications and deletions, the peak intensity of the amplified probes is a very important factor in the analysis. The peak intensity is directly correlated to the copy number in the sample trace. This report may also be saved for printing in Excel.
MLPA Regression Plot
MLPA Intensity Ratio
The software forms a regression line utilizing a standard T distribution. The user may select an Increment or Decrement Regression to locate outliers within the data set. The software identifies outliers based upon a userdefined confidence limit. The report shown above displays the peak intensity ratio between sample and control sample for each amplified probe. The sample to control intensity ratio of probe HIRA in sample B5_11881 is 0.415. The user may also display the intensity of each probe, which in this case is 965 for the sample probe and 2323 for the control.
In order to identify copy number changes within the sample, the software uses the intensity ratios of sample to control. The user can define the thresholds dictating the exonic duplications and/or deletions. The report can display the peak intensity ratio, peak intensity, or peak area. Data points which lie outside the user defined threshold for deletion and duplication (indicated by the horizontal green lines) most likely have some significance for copy number change. The report can be saved as a text file and can be imported into Excel for printing.
*MLPA is a registered trademark of MRC-Holland.
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