Unlock Proteomics Gold

Unlock
Proteomics Gold

from Data Independant Acquisition (DIA) Mass Spectrometry (MS) Data

Please scroll down

Proteins Determine Phenotype

Proteins Determine Phenotype

DIA-MS Does Discovery Proteomics

DIA-MS Does Discovery Proteomics

Yet, ~75-95% of Peptides in DIA-MS Files Are Unused!

Yet, ~75-95% of Peptides in DIA-MS Files Are Unused!

Imagine Unlocking All that Unused "Proteomics Gold" In DIA-MS Data

Many labs have acquired DIA-MS data over the years but have been unable to use ~75-95% of the peptides present in the MS files. Moreover, this ~75-95% set exclusively contains the peptides with unpredicted sequences and unexpected post translational modifications (PTMs) that are far more likely to separate study conditions.

What if we could unlock the hidden value from your past, present, and future DIA-MS data?

For nearly 30 years, discovery-MS proteomics has been promising to outperform genomics, and for good reasons. What if we can help your lab start delivering on that promise? That is, what if, once we quantify the ~75-95% of peptides in DIA-MS files that were previously unquantified, either your lab or ours can integrate in the sample annotation information and then perform straightforward AI / ML to potentially find a predictive panel that separates study conditions?

How might that impact science, publications, patent submissions, your lab, your career, or the general public's lives?

Many labs have acquired DIA-MS data over the years but have been unable to use ~75-95% of the peptides present in the MS files. Moreover, this ~75-95% set exclusively contains the peptides with unpredicted sequences and unexpected post translational modifications (PTMs) that are far more likely to separate study conditions.

What if we could unlock the hidden value from your past, present, and future DIA-MS data?

For nearly 30 years, discovery-MS proteomics has been promising to outperform genomics, and for good reasons. What if we can help your lab start delivering on that promise? That is, what if, once we quantify the ~75-95% of peptides in DIA-MS files that were previously unquantified, either your lab or ours can integrate in the sample annotation information and then perform straightforward AI / ML to potentially find a predictive panel that separates study conditions?

How might that impact science, publications, patent submissions, your lab, your career, or the general public's lives?

Peptides containing unpredicted sequences or unexpected PTMs are up to ~2000% more numerous than peptides identified from a FASTA library search space.

Peptides containing unpredicted sequences or unexpected PTMs are up to ~2000% more numerous than peptides identified from a FASTA library search space.

These unexpected PTMs or unpredicted sequences are far more likely to create a predictive panel that separates your study conditions

These unexpected PTMs or unpredicted sequences are far more likely to create a predictive panel that separates your study conditions

View our preprint or book a web call with our engineers

View our preprint or book a web call with our engineers

Our Innovation:

The best way to learn about our innovation is through an interactive web call. The preprint is a good resource too. Alternatively, for a very quick overview, please see the four figures below.

Global XIC Deconvolution

Book Call (Recommended)

Book a Call

or click on figures to right >>

or see figures below

Our Innovation:

The best way to learn about our innovation is through an interactive web call. The preprint is a good resource too. Alternatively, for a quick overview, please click on the four figures to your right.

Global XIC Deconvolution

Book a Call (Recommended)

or click on figures to right >>

01

PROBLEM

DIA Produces Chimeric XICs

Two co-eluting peptides from a single sample

02

PROPOSED SOLUTION

LC has Natural Variance

Pairs of peptides that co-elute in one subset of samples do not exactly co-elute in another subset of samples

03

MULTIPARTITE MATCHING

Deconvolute Fragments Computationally

Match fragment accross samples to create one clean spectra per peptide

04

QUANTIFICATION & AI

Quantify & Create Predictive Panel

Quantify all analytes in MS and use AI to create predictive panel

Our Innovation:

The best way to learn about our innovation is through an interactive web call. The preprint is a good resource too. Alternatively, for a quick overview, please click on the four figures to your right.

Global XIC Deconvolution

Book a Call (Recommended)

or click on figures to right >>

01

PROBLEM

DIA Produces Chimeric XICs

Two co-eluting peptides from a single sample

02

PROPOSED SOLUTION

LC has Natural Variance

Pairs of peptides that co-elute in one subset of samples do not exactly co-elute in another subset of samples

03

MULTIPARTITE MATCHING

Deconvolute Fragments Computationally

Match fragment accross samples to create one clean spectra per peptide

04

QUANTIFICATION & AI

Quantify & Create Predictive Panel

Quantify all analytes in MS and use AI to create predictive panel

Ready to find peptides that form a predictive panel that separates study conditions?

Ready to possibly
publish or patent the results?

Bonus Benefits

Bonus Benefits

Value Justification

Business Value

Easy Workflow

Easiest Workflow

We Unlock Potentially Astronomical Value From
Past, Present, and Future DIA-MS Data

We Unlock Potentially Astronomical Value From
Past, Present, and Future DIA-MS Data

We quantify the peptides that contain the unpredicted sequences and unexpected PTMs (the ~75- 95% peptides in DIA-MS, an up-to ~2000% increase). These peptides are far more likely to form a predictive panel that separates study conditions.

We quantify the peptides that contain the unpredicted sequences and unexpected PTMs (the ~75- 95% peptides in DIA-MS, an up-to ~2000% increase). These peptides are far more likely to form a predictive panel that separates study conditions.

We are seeking collaborators who are interested in (a) moving quickly, (b) thinking big, and (c) collaborating beautifully.

We are seeking collaborators who are interested in (a) moving quickly, (b) thinking big, and (c) collaborating beautifully.

Book a Call

Book a Call

(C) Copyright GoldenHaystack Lab 2025. All Rights Reserved.

(C) Copyright GoldenHaystack Lab 2025. All Rights Reserved.