YSM Issue 95.2

DECODING MACHINE
LEARNING MYSTERIES
USING ANTS
&
TIME TO MEET YOUR
GREAT NTH GRANDPARENTS
By Eva Syth
Can you create a family tree for all of humanity, dating
as far back as 50,000 generations? A study from
researchers at the University of Oxford says yes, at
least in part. The researchers developed a new method using
data from both contemporary and ancient DNA samples to
construct whole-genome genealogies, providing insights into
human history and evolution.
The researchers combined genetic data from several different
datasets to carry out this study. Historically, this process has
been challenging due to technical errors in the DNA sequencing
process or the use of different DNA sequencing techniques
altogether. The variation stemming from these issues makes it
hard to accurately combine and compare this genetic data because
researchers cannot tell if the differences in sequences are due to
systematic inconsistencies in DNA processing or variation in the
genetic sequences of the samples themselves. To address this issue,
the researchers used “tree sequences,” graphs that represent the
links between regions of DNA in contemporary samples and the
ancestor where the region first appeared. Consider two samples
of DNA: one contemporary and one old. If both samples shared
a significantly similar sequence of nucleotides, they would be
considered “connected” in the graph.
With this challenge solved, the researchers combined eight
datasets and used an algorithm to yield a network of twentyseven
million ancestors. The researchers found that the network
reflected key moments in human history, such as the first human
migrations. Who knows — with this technology, you might be
able to meet your great-great-great…grandparents. ■
By Nathan Wu
What do ant colonies and the Internet have in
common? Both are complex networks that manage
large amounts of traffic. In ant colonies, this traffic
comes from ants scurrying about, while on the Internet, it
comes from packets of data sent between users. In these systems,
computing is “distributed”: system components only know
what is happening locally. Rather than constantly monitoring
everything and making micro-adjustments to keep the system
stable, components respond to specific events, obeying general
algorithms that collectively keep the whole system running.
Scientists at Cold Spring Harbor Laboratory recently found
that ant colonies use additive-increase/multiplicative-decrease
algorithms to forage for food. These are the same algorithms
used by the Internet to manage data traffic. With the Internet,
the system responds by additively increasing the transmission
rate if data is successfully sent and received. If sent data is not
received, the transmission rate is decreased multiplicatively.
Similarly, if an ant foraging for food successfully returns, the
colony will additively increase the number of ants sent, while
if ants fail to return, the number of ants sent out on the next
trip is multiplicatively decreased.
Ant colonies are robust and avoid complete collapse despite
their unpredictable outside environment. Many engineered
systems, however, fail completely at the slightest tampering.
Further study of distributed biological systems may reveal
what makes them so hardy. Perhaps Internet engineers can
learn something from ant colonies—the two are more alike
than they may initially seem. ■
4 Yale Scientific Magazine May 2022 www.yalescientific.org