THE LIFE LABORATORY 生命实验室

4.2 DATA COLLECTION METHODS

THE RESEARCHER

Experience never errs; it is only your judgments that err by promising themselves effects such as are not caused by your experiments.

– Leonardo da Vinci

Phylogenetics explores the evolutionary relationships among organisms, reconstructing the vast history of life. These research results are visualized as branching diagrams known as phylogenetic trees. Today, scientists construct these models by moving beyond purely morphological traits and incorporating massive suites of molecular data. The closer two branches reside, the tighter the evolutionary kinship between the organisms. One of the most captivating frontiers in evolutionary biology is the concept of LUCA – the Last Universal Common Ancestor of all modern cellular life – which allows us to glimpse the absolute foundation of the tree of life. The development of this idea represents an inspiring journey from Charles Darwin’s early hypotheses regarding common descent to cutting-edge contemporary genomic research.

Feeling entirely unique? Phylogenetics offers a gentle reminder: we are part of an exceptionally large and ancient family!

AI & PLANKTON

Researchers at the Irkutsk State University (ISU) Research Institute of Biology, in partnership with Yandex Cloud and Maritime AI, have engineered a neural network to analyze water samples collected from Lake Baikal. Trained on an extensive library of more than 80,000 images, this machine-learning algorithm can accurately identify up to 70 distinct species of endemic Baikal plankton.

SIGNS OF LIFE

Metabarcoding is a revolutionary methodology utilized to detect what is known as environmental DNA (eDNA) within water or sediment samples. A single sample can preserve the microscopic genetic fragments shed by a vast array of organisms. By cross-referencing these genetic sequences against global reference databases, scientists can comprehensively profile every resident inhabiting the studied water body – ranging from bacteria to marine mammals.

NON-INVASIVE DIAGNOSTICS

The SnotBot drone was conceived and developed in 2016 by Dr. Iain Kerr, CEO of the non-profit marine conservation organization Ocean Alliance. The drone collects droplets of the whale’s exhaled breath condensate inside Petri dishes without causing the animal any disturbance. From these samples, scientists study DNA, hormones, and the general condition of the animals.

4.2 数据采集方法

研究者

实验从不骗人,骗人的是我们的判断。

—— 列奥纳多・达・芬奇

系统发生学研究生物亲缘关系,复原演化历史。研究成果绘制成系统发育树。如今构建演化树不只依靠形态特征,同时纳入分子生物学数据;分支距离越近,代表物种亲缘关系越近。演化生物学最激动人心的概念之一,就是LUCA(所有现存细胞生物最后的共同祖先),它带我们追溯到生命之树的根基。这套构想,源自达尔文关于生命拥有共同起源的猜想,一路发展到现代科研成果。

觉得自己独一无二?系统发生学会温柔提醒我们: 我们,只是庞大而古老生命大家庭当中的一员。

人工智能与浮游生物

伊尔库茨克国立大学生物研究所科学家,联合Yandex Cloud、Maritime‑AI开发神经网络,用于分析贝加尔湖水样。该模型学习八万余张图像,可以识别70种贝加尔湖浮游生物。

生命的痕迹

环境DNA宏条形码技术(eDNA metabarcoding)是一种通过分析水样或沉积物样本中的环境DNA来识别生物类群的方法。一份样本内,可以留存大量生物的基因片段。把基因片段与数据库比对,就可以获知这片水域曾经/现在生存哪些生物,小到细菌,大到哺乳动物。

非侵入性诊断

斯诺特博特(SnotBot)2016年由海洋联盟(Ocean Alliance)非营利组织伊恩・科尔发明并开发。斯诺特博特在鲸鱼呼气时用培养皿收集水滴,而不打扰动物。科学家通过这些样本研究DNA、激素和动物的总体状况。