CLIQS Series
SDS-PAGE, Agarose gel 및 Western blots을 대상으로 간단한 DNA 정량 및 Protein array, Dot blot, Colony counting 분석을 하는 프로그램
Dendrogram 지원
band matching 기능을 갖는 1D gel 자동 분석
휘고 찌그진 band 자동 인식하여 사용 편리
자동 background 보정
결과를 엑셀형태 (position, mm, inch, Rf, Mw) 로 저장
- Molecular Biology
- Microbiology
- Biochemistry
- Virology
- Cell Biology
- Genetics
- Proteomics
- Evolutionary Biology
- Neuroscience
For 1D gels, highly developed algorithms accurately detect lanes and bands even on distorted gel images. Results can be verified using the range of visualization tools which aid further examination of lane and band data.
Calibrate the bands using one or more Molecular Size standard lanes and derive accurate quantitation from known band volume
For the Arrays and Colony plates, rapid identification and quantitative measurements of all relevant features allow for speedy analysis and accurate data
Compare lanes from multiple gels and experiments. It allows a completely flexible approach to matching. Each individual lane can be compared to any other lane within the database. The results of matching across many gels can be presented as a dendrogram or tables that show all the band and lane similarities.
For the Arrays and Colony plates, rapid identification and quantitative measurements of all relevant features allow for speedy analysis and accurate data
Identify lane relationships across many experiments. Clustering lanes using dendrograms, allows you to the study the relationships between lanes stored in the database. These dendrograms are easy to create from the match results. Once built, the dendrogram is scalable and fully interactive, to allow a flexible presentation of lane relationships. The dendrogram also allows you to create groups of related lanes that can then be reported on in a cluster table.
Classify unknown samples. Lanes containing unknown samples can be identified and classified against a defined reference library of identified samples. Maintenance of the library is very straightforward and it can be easily shared with co-workers to facilitate collaboration on large projects
Classify unknown samples. Lanes containing unknown samples can be identified and classified against a defined reference library of identified samples. Maintenance of the library is very straightforward and it can be easily shared with co-workers to facilitate collaboration on large projects
All common image formats can be analysed. Maximise the use of image capture instruments you already have in your lab
