The present disclosure provides machine learning techniques for computationally predicting the phenotypic performance of combinations of genetic variations and for designing new improved host cells. The machine learning models and methods described herein are host agnostic and therefore can be implemented across taxa. Furthermore, the disclosed platform can be implemented to modulate or improve any host cell parameter of interest.

The present disclosure provides a HTP microbial genomic engineering platform that is computationally driven and integrates molecular biology, automation, and advanced machine learning protocols. This integrative platform utilizes a suite of HTP molecular tool sets to create HTP genetic design libraries, which are derived from, inter alia, scientific insight and iterative pattern recognition. The HTP genomic engineering platform described herein is microbial strain host agnostic and therefore can be implemented across taxa. Furthermore, the disclosed platform can be implemented to modulate or improve any microbial host parameter of interest.

A sample processing station includes two or more container holders on a platform that is rotatable about a central axis of rotation. Each holder is configured to rotate about a secondary axis of rotation. The station includes a capping/decapping mechanism to cap or decap a container held in one of the container holders and a drip tray movable between a first position not under the capping/decapping mechanism and a second position under the capping/decamping mechanism.

Temperature adjustment with a pipette tip temperature adjustment unit (7) and a drive unit (54) for raising and lowering a pipette tip (51), an environment temperature sensor (10) for sensing temperature inside an analysis apparatus (1A), a pump (53) for drawing a liquid into pipette tip (51) and discharging liquid in the pipette tip (51), and a control unit (6a) for setting, in advance, temperature control target value during sample analysis for unit (7) based on environment temperature sensed by sensor (10), and during sample analysis, drive unit (54) lowers pipette tip (51), pump (53) performs pumping wherein intake and discharge are repeated in a state in which unit (7) blows air, and unit (6a) sets, in advance, the temperature value for use during sample analysis for the pipette tip temperature adjustment unit (7) on the basis of analysis reagent information and the environment temperature sensed by e sensor (10).

The present disclosure provides a HTP microbial genomic engineering platform that is computationally driven and integrates molecular biology, automation, and advanced machine learning protocols. This integrative platform utilizes a suite of HTP molecular tool sets to create HTP genetic design libraries, which are derived from, inter alia, scientific insight and iterative pattern recognition. The HTP genomic engineering platform described herein is microbial strain host agnostic and therefore can be implemented across taxa. Furthermore, the disclosed platform can be implemented to modulate or improve any microbial host parameter of interest.

Systems and methods for handling a variety of sample and preparatory fluids in a rack specifically configured for compatibility with predetermined liquid handlers such as automated pipettors or multi-channel manual pipettors and set up for magnetic based sample preparation. The rack can hold all of the necessary sample and reagent vials, and present them to the pipettor in some embodiments in a way that allows for parallel operation. The rack includes slidable magnets that in some embodiments are actuatable directly by the pipettor, eliminating a layer of complexity. Combined with a suitable pipettor the magnet enabled rack supports a multistep magnetic based sample preparation capability in a high throughput manner at one station that enhances sample purity throughout magnetic separation processes.

The present disclosure provides a HTP microbial genomic engineering platform that is computationally driven and integrates molecular biology, automation, and advanced machine learning protocols. This integrative platform utilizes a suite of HTP molecular tool sets to create HTP genetic design libraries, which are derived from, inter alia, scientific insight and iterative pattern recognition. The HTP genomic engineering platform described herein is microbial strain host agnostic and therefore can be implemented across taxa. Furthermore, the disclosed platform can be implemented to modulate or improve any microbial host parameter of interest.

The present invention is directed generally to devices and methods for manipulating laboratory pipettes in a programmable manner. The present invention is directed to an apparatus and methods for allowing a user to instruct the device to perform a specific process; identifying the type, location and identity of the consumables to be used; manipulating a plurality of pipettes for performing the liquid handling; monitoring the process during and after its execution; generating a detailed report for the plurality of actions. Other aspects of this invention include optimization of the liquid dispensing performances of a pipette; monitoring and controlling individual actions by means of vision; virtualization of the protocol definition by means of a reality augmented software interface; integration of the system in a conventional laboratory environment workflow.

The invention relates to a measuring apparatus for detecting the relative position of an end portion of a pipetting container by an interaction between a measurement support section of the pipetting container and the measuring apparatus. The invention relates to an automatic laboratory, which comprises this measuring apparatus and to a corresponding measuring method.

A sample container of patient sample material includes a sample container barcode containing patient-identifying information. The sample container barcode on the sample container is read, and a tubular reaction vessel is provided to a printer module configured to print a barcode directly onto a surface of the tubular reaction vessel. The printer module prints a barcode on the surface of the reaction vessel by a thermal printing method, and the barcode printed onto the reaction vessel is associated with the sample container barcode.