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441 results for “titration”
IODP Expedition 383 Titration
Various chemical constituents (most commonly chloride) were measured by titration using either an autotitrator (chloride) or a manual titrator (other compounds). Chloride was measured by ion-selective electrode and a silver nitrate titration until all chloride is bound as silver chloride.
IODP Expedition 367 Titration
Various chemical constituents (most commonly chloride) were measured by titration using either an autotitrator (chloride) or a manual titrator (other compounds). Chloride was measured by ion-selective electrode and a silver nitrate titration until all chloride is bound as silver chloride.
Data for Publication: "Automated Investigation of Metal-Ligand Interactions by a Newly Established Robotic Workflow for Titrations"
<p>This dataset contains the whole primary and raw (original) data for the manuscript "Automated investigation of metal-ligand interactions by a newly established robotic workflow for titrations".</p>
High-throughput robotic titration using computer vision
<ul> <li> <p>An automated HTE robotic titration using a liquid-handling robot Opentrons(OT-2) and a standard webcam enables in-situ, affordable titration analyses.</p> </li> <li>Its modular design allows adaptability for materials chemsitry and integration into automated workflows, enhancing efficiency in chemical search.</li> </ul>
Datasets of titrations of mineral water hardness monitored using SERS
<p>These datasets contains the spectral information used in a publication regarding the implementation of complexometric titrations of water hardness monitored using Surface Enhanced Raman Spectroscopy (SERS).</p> <p>The data consists of two csv files with semi-column separators.</p> <p><em>« MD150 to 155_Master_df_638_corrected_mod_v02.csv »</em> and <em>« MD150 to 155_Master_df_785_corrected_mod_v02.csv »</em> correspond to spectral data acquired under 638 and 785 nm irradiation respectively.</p> <p>The data are organised as row vectors.</p> <p>Each dataset has 432 rows corresponding to 3 water samples (Evian, Volvic, Contrex), 3 replicate titration series + 1 blank titration per batch of NPs, 2 batches of NPs and 18 titration steps per titration series: .</p> <p>The row vectors consist of a first sub-vector of spectral descriptors (identity of spectra, identity and composition of measurement samples and conditions of spectral acquisition), followed by a sub-vector of baseline-substracted spectral intensities.</p> <p>In both datasets, the first 14 columns consists of the spectral descriptors.</p> <p>In the <em>« MD150 to 155_Master_df_638_corrected_mod_v02.csv » </em>dataset, the spectra section consists of 1010 columns which names are the values of the Raman shifts at which the intensities have been recorded.</p> <p>In the <em>« MD150 to 155_Master_df_785_corrected_mod_v02.csv »</em> dataset, the spectra section consists of 1746 columns which names are the values of the Raman shifts at which the intensities have been recorded.</p>
IODP Expedition 379 Titration
Various chemical constituents (most commonly chloride) were measured by titration using either an autotitrator (chloride) or a manual titrator (other compounds). Chloride was measured by ion-selective electrode and a silver nitrate titration until all chloride is bound as silver chloride.
IODP Expedition 371 Titration
Various chemical constituents (most commonly chloride) were measured by titration using either an autotitrator (chloride) or a manual titrator (other compounds). Chloride was measured by ion-selective electrode and a silver nitrate titration until all chloride is bound as silver chloride.
IODP Expedition 397 Titration
Various chemical constituents (most commonly chloride) were measured by titration using either an autotitrator (chloride) or a manual titrator (other compounds). Chloride was measured by ion-selective electrode and a silver nitrate titration until all chloride is bound as silver chloride.
Titration_DB: NMR-monitored protein pH titration chemical shift data.
<p>This archive contains a backup of the NMR titration_db database raw chemical shift data.<br> Reference: D. Farrell et al., “Titration_DB: Storage and analysis of NMR-monitored protein pH titration curves.,” Proteins, vol. 78, no. 4, pp. 843–857, 2009.</p> <p>This data was formerly hosted on an interactive website which is no longer active. The files are stored as csv format, one per protein. They are also split into three folders according to the nuclei whose chemical shifts were used to detect the measurement (1H,13C or 15 N). Much of this data was obtained from literature. A table in the zip file (titration_dataset_info.csv) associates the protein name with the original paper. </p> <p>Note that the database stored the pka values fit using a model to each residue dataset. This is not stored here.</p> <p>Also present is a file titdb.fs. This is a binary file that can only be opened using the PEATDB software. PEATDB (Protein Engineering Analysis Tool - Database) was an application for sharing, analysing and storing experimental and theoretical data from Protein Engineering experiments.<br> This is now legacy software and no longer maintained. It was used to allow interactive fitting of the titration data using the Ekin module.<br> It is still possible to install this software if you really need to. It is stored on github at https://github.com/dmnfarrell/peat.</p> <p>D. Farrell May 2019</p>
Datasets of pushing complexometric titrations in the nanomolar range thanks to SERS
<p>These datasets contains the spectral information used in a publication regarding the implementation of complexometric titrations of copper monitored using Surface Enhanced Raman Spectroscopy (SERS). In this study the sensitivity of a classic complexometric titration system for Cu2+ is pushed into the nanomolar regime thanks to SERS monitoring of the endpoint.</p> <p>All the data are organised as column vectors. </p> <p>The data consists of three csv files with semi-column separators.</p> <p>“AN334_and_AN338_laser_532nm_1microM_copper_variation_of_PAN_all_data_corrected_serie_11_points” correspond to spectral data acquired under 532 nm irradiation with variation of the PAN (100, 50 and 25 nM) concentration for 1 µM of copper.</p> <p>“AN335_and_AN341_laser_532nm_500nM_copper_variation_of_PAN_all_data_corrected_serie_11_points” correspond to spectral data acquired under 532 nm irradiation with variation of the PAN (100, 50 and 25 nM) concentration for 500 nM of copper.</p> <p>“AN336_and_AN344_laser_532nm_250nM_copper_variation_of_PAN_all_data_corrected_serie_11_points” correspond to spectral data acquired under 532 nm irradiation with variation of the PAN (100, 50 and 25 nM) concentration for 250 nM of copper.</p> <p>Each dataset has 90 685 rows corresponding to 1 irradiation used (532 nm), 2 experimental replicate titration series including 1 titration + 1 blank titration for each titration and for 3 differents concentrations of PAN and 11 titration steps per titration series. For the 3 copper concentrations we obtain 396 samples.</p> <p>The columns vectors consist of a first sub-vector of spectral descriptors (identity of spectra, identity and composition of measurement samples and conditions of spectral acquisition), followed by a sub-vector of baseline-subtracted spectral intensities.</p> <p>The meaning of each column is in the .docx file titled "Structure of AN334-AN338 to AN336-AN344 datasets”.</p> <p>The other two csv fils with semi-column separators "AN339_AN342_AN345_laser_638nm_variation_of_copper_and_PAN_all_data_corrected_serie_11_points" and "AN340_AN343_AN346_laser_785nm_variation_of_copper_and_PAN_all_data_corrected_serie_11_points" correspond to spectral data acquired under 638 and 785 nm irradiation respectively. In both files, the data correspond to the 11-point experiments with PAN variation (100, 50 and 25 nM) and copper variation (1 µM, 500 and 250 nM).</p> <p><span>Finally, the data consists of one csv files with semi-column separators.</span></p> <p><span>“AN384_to_AN386_Laser_532_638_785nm_all_data_corrected_titration_serie_20_points” correspond to spectral data acquired under 532, 638 and 785 nm irradiation.</span></p> <p><span>The dataset has 111 241 rows corresponding to 3 irradiations used (532, 638 and 785), 2 replicate titration series + 1 blank titration and 20 titration steps per titration series.</span><span></span></p> <p><span>The columns vectors consist of a first sub-vector of spectral descriptors (identity of spectra, identity and composition of measurement samples and conditions of spectral acquisition), followed by a sub-vector of baseline-subtracted spectral intensities.</span></p> <p>The meaning of each column is in the .docx file titled "Structure of AN384 to AN386 datasets”.</p>
Supplementary material for journal article "Challenge dose titration in a Mycobacterium bovis infection model in goats"
<p>Supplementary Figure and Table to Journal article. Figure shows daily rectal temperature of each animal after inoculation. Table 1 shows number and volume of pulmonary lesions for each animal as detected by computed tomography imaging. Table 2 gives details about scoring used at clinical examination.</p>
IODP Expedition 353 Titration
Various chemical constituents (most commonly chloride) were measured by titration using either an autotitrator (chloride) or a manual titrator (other compounds). Chloride was measured by ion-selective electrode and a silver nitrate titration until all chloride is bound as silver chloride.
IODP Expedition 359 Titration
Various chemical constituents (most commonly chloride) were measured by titration using either an autotitrator (chloride) or a manual titrator (other compounds). Chloride was measured by ion-selective electrode and a silver nitrate titration until all chloride is bound as silver chloride.
IODP Expedition 362 Titration
<p>Various chemical constituents (most commonly chloride) were measured by titration using either an autotitrator (chloride) or a manual titrator (other compounds). Chloride was measured by ion-selective electrode and a silver nitrate titration until all chloride is bound as silver chloride.</p>
IODP Expedition 366 Titration
<p>Various chemical constituents (most commonly chloride) were measured by titration using either an autotitrator (chloride) or a manual titrator (other compounds). Chloride was measured by ion-selective electrode and a silver nitrate titration until all chloride is bound as silver chloride.</p>
IODP Expedition 372A Titration
<p>Various chemical constituents (most commonly chloride) were measured by titration using either an autotitrator (chloride) or a manual titrator (other compounds). Chloride was measured by ion-selective electrode and a silver nitrate titration until all chloride is bound as silver chloride.</p>
IODP Expedition 352 Titration
<p>Various chemical constituents (most commonly chloride) were measured by titration using either an autotitrator (chloride) or a manual titrator (other compounds). Chloride was measured by ion-selective electrode and a silver nitrate titration until all chloride is bound as silver chloride.</p>
IODP Expedition 351 Titration
<p>Various chemical constituents (most commonly chloride) were measured by titration using either an autotitrator (chloride) or a manual titrator (other compounds). Chloride was measured by ion-selective electrode and a silver nitrate titration until all chloride is bound as silver chloride.</p>
NMR titration experiments that study binding of a NIR emitting osmium polypyridyl probe to cMYC and hTel G-quadruplex DNA
<p>1D and 2D NMR spectra of cMYC and hTel G-quadruplex DNA and their complexes with Λ-<strong> </strong>and Δ<strong>-</strong>enantiomers of the osmium polypyridyl probe [Os(TAP)<sub>2</sub>(dppz)]<sup>2+</sup>. Spectra were recorded on a 600 MHz NMR spectrometer with 70 mM KCl, 20 or 25 mM K-phosphate buffer, pH 7, 298 K, in 90% H<sub>2</sub>O and 10% D<sub>2</sub>O at 25 °C.</p>
SAXS-based titrations of periplasmic binding proteins against known ligands
<p>This dataset contains the small-angle X-ray scattering intensities of a series of titrations between proteins HisBP, GlnBP, and DEBP against a number of amino acids. A total of five synchrotron beamline sessions are included to test for reproducibility across setups and total exposure time per sample:</p> <ul> <li>DESY P12 (4s)</li> <li>ESRF BM29 (5s)</li> <li>Australian Synchrotron SAXS/WAXS (20s)</li> <li>Diamond B21 (40s)</li> </ul> <p>The accompanying manuscripts can be found on bioRxiv MS 715193, entitled: "Structure-based screening of binding affinities via small-angle X-ray scattering". It is currently under consideration with te Biophysical Journal.</p>
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