StrainControl Laboratory Information Management System

Straincontrol Laboratory Manager

Straincontrol Is A Windows-based Management Software For People Working In A Lab. Straincontrol Manages Bacterial Strains, Plasmids, Oligos, Antibodies And Physical Inventories. Every Lab Needs Straincontrol. StrainControl Laboratory Manager is a windows-based software that allows you to organize collections of strains, plasmids, oligos, antibodies and inventories. In most laboratories, there is a growing need for storing this information in an efficient and secure way. Although the need is something most laboratories feel every day, there is a lack of good softwares that do precisely this. StrainControl Laboratory Manager covers all aspects of an excellent Lims software designed to help organizing your lab. If you already have your collections in a word- or data processor simply use the built-in guide to import all data into StrainControl Laboratory Manager. Fast and easy. After this all your data will be searchable and organized in an efficient and secure manner.

Straincontrol Laboratory Manager Summary

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Integration with LIMS

Each can be developed and tested independently. The laboratory system is expected to produce a file with a particular format - that can be verified. The LIMS can be tested with files that conform to the expected file format, synthesized based on the specification. Now it must be shown that the LIMS can accept and integrate the files from the data system I All of the testing should be done on a LIMS test-bed data base,

Array Express an Example of a Public Repository

ArrayExpress is an international repository for gene expression data, which uses the MAGE-OM model. The MAGE-OM model is an (array) platform independent data model which can equally represent data from single and dual channel experiments. This means that data from various LIMS databases, manufacturers and public databases can be mapped to MAGE and data exchanged in the same format -MAGE-ML. As MAGE is now an adopted OMG standard there has been significant take-up of the format and SMD, TIGR, RZPD, Agilent, Affymetrix and others are now making data and array designs available in MAGE-ML format.

Validation Requirements Chemistry or Computer

Environmental Protection Agency (US EPA) issued a Good Automated Laboratory Practices (GALP) document in 1990 that applies to all laboratories that provide data to US EPA 11 . This document gives thorough recommendations for implementing and operating an automated laboratory however, each section of the GALP manual specifically states that its recommendations apply to automated data collection systems and Laboratory Information Management Systems (LIMS). No mention is made of automated sample preparation systems. United States Food and Drug Administration (FDA) has also recommended procedures for validation of computer software and hardware that are used for systems that collect, report, and store raw data, such as data acquisition systems, and LIMS. Like GALP, those regulatory policies do not refer to validations performed on automated laboratory robotic systems and workstations used for sample preparation.

Obtaining the Initial Target Protein Structure

At SGX, de novo protein crystal structures are determined using a gene-to-structure platform that was developed to process multiple proteins in parallel. This platform consists of modular robotics and a comprehensive laboratory information management system (LIMS) that facilitates data entry and electronic data capture at all stages of the process. The LIMS system also permits comprehensive data mining for troubleshooting and project management. The SGX gene-to-structure platform has facilitated high-resolution (typically better than 2 ) structure determinations for a large number of drug discovery targets, including more than 50 unique human protein kinases and a large number of nuclear hormone receptor ligand-binding domains. Successes include many targets not represented in the public domain Protein Data Bank 30 , some of which are regarded as being extremely difficult if not impossible to express, purify, and crystallize.

Fragment Library Screening at SGXCAT

Periments are tracked in the SGX LIMS system, which is accessible from SGX-CATat the APS. Direct T1 line connectivity permits rapid data transfer between the two sites. Once the frozen crystals are transported to SGX-CAT by courier, pertinent sample information is accessed from the LIMS system and the samples are loaded into data collection carousels. Multiple data collection carousels may be stored in liquid nitrogen and queued for automated data collection. When a carousel is ready for analysis, it is transferred from the storage dewar to the Mar crystal mounting robot 32 . Data collection processing parameters are retrieved from the SGX LIMS system to control both the progress of the diffraction experiment and data processing in real time. Reduced diffraction data are automatically transferred back to SGX headquarters in San Diego via our dedicated T1 line and experimental parameters are captured by the SGX LIMS database. This system permits routine, unattended data collection from...

Analysis of Fragment Screening Results

Automated processing of diffraction data is performed using a system that combines proprietary SGX software and the CCP4 33 program package. For each screening attempt with a ten-compound, shape-diverse mixture, the structure of the target protein is automatically re-determined by molecular replacement using a reference target structure pre-defined in the SGX LIMS. The reference structure is generally the best representative for that target, as defined by resolution limit, R-factor, and overall data structure quality. Once this step is complete, difference Fourier syntheses are calculated to reveal any superficial electron density features that cannot be explained by either the protein or water molecules (see Fig. 11.1B for an example). For each unexplained electron density feature, an attempt is made to automatically identify the fragment within the mixture that best corresponds to the shape of the electron density. The output of this analysis may then Once the automated processing...

Informatics and Databases

When more than one person is involved in the process, it can be useful to store the data in a database. There are two main reasons for doing this Firstly, a Laboratory Information Management System (LIMS) database is useful to keep track of who has done what to which experiments and other useful information in the initial production of data. This is important when one wants to track the workflow of technicians running the biological processes to make the chips. Many vendors (such as Affymetrix) provide LIMS that work with their systems. Unfortunately, like all LIMS, it is often desired to have a LIMS that fits in perfectly with the local work flow, and this requires extensive customization.

Using surveillance data to characterize and analyze risk factors for foodborne illness

Historically, evaluating the magnitude of foodborne disease in developed countries relied on statistics on foodborne illness from 'passive' surveillance. Passive surveillance methods require clinical microbiology laboratories and physician's offices to report cases of foodborne disease to state, provincial, and or regional health departments which in turn communicate to a national entity such as the US Centers for Disease Control and Prevention (CDC). Several systems based on this principle exist at the national level in the United States (CDC, 1997 Mead et al., 1999) the National Notifiable Disease Surveillance System (NNDSS), the Public Health Laboratory Information System (Salmonella and Shigella), and the Foodborne Disease Outbreak Surveillance System. The Foodborne Disease Outbreak Surveillance System contains data on more than 20 000 US foodborne disease outbreaks reported to the CDC since 1973 (Batz et al., 2005). Perhaps most importantly, the Foodborne Diseases Active...

Statement of Need and Product Requirements

A method is needed to acquire data from a balance during the course of a gravimetric analysis and perform calculations. The results of the calculations and the data used, should be put into a format that can be read by a LIMS without having to manually reenter any of the data. After careful consideration, it is decided that a computer will be used to capture the data, perform the results, and prepare an ASCII file that can be read by any LIMS system, given a known file format. The product requirements for the software are Have local storage to load programs and hold data for transmission to the LIMS Support communications to the balance and LIMS - over separate communication lines

Engineering Response to Requirements

The specifications should contain a list of the qualification criteria for computer hardware and software to be used for the project and the final target production system. In addition any changes to the LIMS system should be determined and a separate engineering schedule should be designed to meet those development requirements, including how the file from the lab data system is going to be transferred to the LIMS and incorporated into its data structure (note this is the equivalent of magic happens here in some cartoons, our intent is to outline a project not give the details of its implementation).

Figure 121

We will also look at the direction that laboratory computing technology is taking, its impact on systems design and validation, and the possible problems that can occur as newer operating systems, tools and non-traditional programming environments develop. In doing this work we will make one departure from current practices. Laboratory computer information systems (applications - both commercial and custom developed, OS, and hardware) are usually treated as a collection of independent entities. One may validate a Laboratory Information Management System (LIMS), or a data acquisition analysis system, or a robotics system, each as an independent entity. The view of this author is that these should be treated as part of a laboratory-wide system and designed as such 3 . The intent of this chapter is to provide an overview of the considerations that should be taken into account in the development of validation programs for laboratory computer systems, networks, and automated equipment....