How Many Digits of a Peptide Purity Result Are Real? Measurement Uncertainty Explained
Why HPLC peptide purity figures carry measurement uncertainty, how large it typically is, and how to compare 98.7% and 99.3% without over-reading them.
Reading New Peaks: How Light, Oxygen and Temperature Degrade Peptides
How peptides degrade through oxidation, light, deamidation, hydrolysis and aggregation, with the mass shifts and HPLC signs that identify each pathway.
Reporter Gene Assays With Peptides: From Light Output to Receptor Claims
How reporter gene assays turn receptor signaling into light, why peptide curves can mislead, and the controls that tie a response to one receptor.
Designing Vehicle Controls for Peptide Experiments
Why vehicle controls matter in peptide experiments, how counter-ions and solvents confound results, and the four most common control design errors.
Diode Array Peak Purity: Reading a Pass or Fail on a Peptide Peak
How diode array peak purity checks work in peptide HPLC, why a pass is weaker than a fail, and which impurities share a spectrum and stay hidden.
MALDI or ESI: How Ionization Shapes Peptide Mass Evidence
How MALDI and electrospray ionization differ for peptides, why charge state affects one-dalton distinctions, and what to check on a mass result.
Reading Protecting Group Masses in Synthetic Peptide Impurities
How to identify incomplete deprotection from mass shifts such as +56, +222, +242 and +252 Da, and how to tell retained groups from re-alkylation.
Western Blots as Evidence: What a Band Can and Cannot Show
What a western blot band really shows, why small peptides are often lost in gels and membranes, and why band intensity is a weak quantitative measure.
Peptide Sample Preparation for HPLC: What Happens Before the Run
How solvent strength, adsorption, filtration, autosampler time and overload distort peptide HPLC results, and how analysts diagnose each problem.
Reading a p-Value Without Overreading It
What a p-value measures, the four common misreadings, how multiple comparisons and small studies mislead, and why effect sizes with intervals matter.