Liat Shenhav Profile picture
Feb 10 11 tweets 6 min read
📢New paper out in @mSystemsJ, coauthored w/ the amazing @MeghanAzad!
Inspired by community #ecology theory and computational #microbiome methods, we propose a novel strategy for studying #humanmilk.

journals.asm.org/doi/10.1128/ms…
We focused on 3 major barriers to understanding #breastmilk
1⃣Milk contains thousands of components, yet most studies analyze just one or a few
2⃣Milk changes over time, yet longitudinal studies are rare
3⃣We lack computational tools & methods to study milk as a complex SYSTEM
From a #DataScience perspective, to study complex biological processes such as #humanmilk and lactation, it is essential to take an integrative and ‘multi-layer’ approach.
Nonetheless, it is computationally challenging to integrate signals from multiple modalities - especially temporal ones - in a unified model. We therefore propose leveraging methods developed to study another complex system - the #microbiome.
We showcase the wide array of parallels between #humanmilk and the microbiome and demonstrate how incorporating knowledge gleaned from community ecology and computational microbiology can serve as an anchor to advance the study of #humanmilk as a system.
We further suggest that #humanmilk is a complex adaptive system, in which low-level local interactions and selection mechanisms combine to create high-level patterns.
In the unique case of #humanmilk, it originates in the mother but its properties emerge in the infant, emphasizing the importance of the mother-milk-infant “triad” and its environment as the unit of study. Image
To fully unlock the potential of this approach, we advocate to Record, Represent and Decipher the mother-milk-infant “triad” during the course of lactation.
Longitudinal, multi-layer #humanmilk studies, along with tailored computational methods, may lead to identification and characterization of milk interactions and dynamics that are associated with optimal health outcomes. Image
WATCH our video summary:
We’re excited to apply this multi-layered approach to #humanmilk research, and hope our paper will inspire others to do the same.
Thank you @gilbertjacka for the invitation to share our ideas in your special issue!
#transdisciplinary #DataScience #breastmilk #microbiome

• • •

Missing some Tweet in this thread? You can try to force a refresh
 

Keep Current with Liat Shenhav

Liat Shenhav Profile picture

Stay in touch and get notified when new unrolls are available from this author!

Read all threads

This Thread may be Removed Anytime!

PDF

Twitter may remove this content at anytime! Save it as PDF for later use!

Try unrolling a thread yourself!

how to unroll video
  1. Follow @ThreadReaderApp to mention us!

  2. From a Twitter thread mention us with a keyword "unroll"
@threadreaderapp unroll

Practice here first or read more on our help page!

More from @LiatShenhav

Nov 10, 2020
We did it, @DaveZeevi! Our paper is now published in @ScienceMagazine! science.sciencemag.org/content/370/65…
We present a data-driven, computational perspective on how selective pressures resulting from nutrient limitation shape microbial coding sequences. Thread below:
We study ‘resource-driven’ selection using metagenomic and single-cell data of marine microbes, while adopting concepts common in statistical genetics like linear mixed models with variance components. Image
Using tailored algorithms, we partition the variance in selection metrics, calculated using marine microbes, and show that a significant portion of the selection is explained by the environment and is associated with nitrogen availability. Image
Read 10 tweets
Aug 31, 2020
Our paper on Compositional Tensor Factorization (CTF) of microbial dynamics is now published in @NatureBiotech! nature.com/articles/s4158…
It might change how you analyze longitudinal microbiome data. Thread below:
This work was a great collaboration and fun with
@cameronmartino and @lisa55asil, George Armstrong, @mcdonadt, @yoshikivb, @jamietmorton, Lingjing Jiang, Maria Gloria Dominguez-Bello,@CMI_Austin, @halperineran, @KnightLabNews. Thank you!!
In a cross-sectional study, you run a PCoA and look at the top PCs. But with temporal data, applying PCoA separately on each time point may mask important information that is carried over time.
For your longitudinal data analysis you should use CTF!
Read 8 tweets

Did Thread Reader help you today?

Support us! We are indie developers!


This site is made by just two indie developers on a laptop doing marketing, support and development! Read more about the story.

Become a Premium Member ($3/month or $30/year) and get exclusive features!

Become Premium

Don't want to be a Premium member but still want to support us?

Make a small donation by buying us coffee ($5) or help with server cost ($10)

Donate via Paypal

Or Donate anonymously using crypto!

Ethereum

0xfe58350B80634f60Fa6Dc149a72b4DFbc17D341E copy

Bitcoin

3ATGMxNzCUFzxpMCHL5sWSt4DVtS8UqXpi copy

Thank you for your support!

:(