The largest database of trusted experimental protocols

Igor pro version 6.22a

Manufactured by Wavemetrics
Sourced in United States

Igor Pro is a data analysis and visualization software developed by Wavemetrics. It is a powerful tool designed to help researchers, engineers, and scientists efficiently analyze and interpret their data. Igor Pro (Version 6.22A) offers a wide range of features for data processing, statistical analysis, and graphical representation, making it a versatile solution for various scientific and technical applications.

Automatically generated - may contain errors

3 protocols using igor pro version 6.22a

1

Synchrotron SAXS Characterization Protocol

Check if the same lab product or an alternative is used in the 5 most similar protocols
Synchrotron X-ray scattering data was collected at the Austrian SAXS beamline at ELETTRA (Trieste, Italy) [48 ]. Measurements were conducted at a wavelength of 0.154 nm and a sample-detector distance of 1.1 m. The photon energy was 8 keV. Data was recorded with a Pilatus detector (PILATUS 100K, DECTRIS Ltd., Villigen PSI, Switzerland), calibrated with silver behenate. The scattering intensity was measured as a function of the scattering vector q where
q=4π(sinϑ)λ
with 2ϑ being the scattering angle and λ being the wavelength. Samples were measured either in a 1.5 mm glass capillary (10-60 mM) or in a gel sample holder (75 mM). A discussion on the influence of shearing forces when filling the capillary can be found in the ESM (Table S7 and Fig. S8). Data analysis was done with Fit2D [49 ] and Igor Pro (Version 6.22A, WaveMetrics Inc., USA). Experimental intensities were normalized to the sample transmission and corrected for background. Absolute calibration was done by using water as secondary standard after the method described by Orthaber [50 ].
+ Open protocol
+ Expand
2

FLIM Analysis of Protein-Protein Interactions

Check if the same lab product or an alternative is used in the 5 most similar protocols
FLIM experiments were performed on an Olympus FluoView 1000 laser scanning microscope (Olympus, Tokyo, Japan) with a Sepia II and PicoHarp 300 time correlated single photon counting system from PicoQuant (Berlin, Germany). Proteins were tagged with the fluorescent proteins mCitrine (donor) and mCherry (acceptor) to optimize FRET efficiency. All experiments were carried out at 37°C with a 60x water objective. For imaging, samples were simultaneously excited with 488 (10% laser intensity) and 561 nm (31% laser intensity) light using a 405/488/561/633 dichroic mirror. Excitation light was split with a dichroic mirror at 560 nm and detected between 500–550 nm (green channel) and 580–680 nm (red channel). The pinhole was set to 300 μm. FLIM images were acquired using 470 nm excitation (36% intensity) with a pulse frequency of 40 MHz, a 405/470 dichroic mirror, and a 525/15 band path filter. FLIM images were analyzed using IGOR Pro (Version 6.22 A, Wave Metrics, Lake Oswego, OR) with pFLIM3 as previously described (Walther et al., 2011 (link)).
+ Open protocol
+ Expand
3

Extracting Diving Behavior Metrics from Depth Data

Check if the same lab product or an alternative is used in the 5 most similar protocols
After recovery, raw data were downloaded from the loggers and analyzed using Igor Pro version 6.22A (Wavemetrics Inc.). We used a purpose‐written script to adjust the depth to zero when birds were at the surface between two dives and extract diving parameters from the depth data, including maximum diving depth, dive and postdive duration, and the number of vertical undulations in the bottom phase of the dive for each dive deeper than 1 m, which are generally indicative of prey pursuit (Kato, Ropert‐Coudert, Grémillet, & Cannell, 2006; Ropert‐Coudert, Kato, Wilson, & Cannell, 2006). A bottom phase was defined as the first and last time during a dive that the depth‐change rate became <0.25 m/s (Kato, Ropert‐Coudert, & Chiaradia, 2008). To allow comparison between the different stages, we calculated the mean foraging effort per day as the total diving duration (in minutes) divided by the trip duration (in days). Similarly, we calculated the mean number of dives per day as the total number of dives performed over a trip divided by the trip duration (in days). The prey encounters per unit time used as proxy for foraging efficiency was calculated as the total number of vertical undulations divided by the total diving duration over the trip (Sala, Wilson, & Quintana, 2012).
+ Open protocol
+ Expand

About PubCompare

Our mission is to provide scientists with the largest repository of trustworthy protocols and intelligent analytical tools, thereby offering them extensive information to design robust protocols aimed at minimizing the risk of failures.

We believe that the most crucial aspect is to grant scientists access to a wide range of reliable sources and new useful tools that surpass human capabilities.

However, we trust in allowing scientists to determine how to construct their own protocols based on this information, as they are the experts in their field.

Ready to get started?

Sign up for free.
Registration takes 20 seconds.
Available from any computer
No download required

Sign up now

Revolutionizing how scientists
search and build protocols!