Science — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-FP8, prompt version 1) read this channel’s own recent posts on 11 September 2026 and assigned it the closest of 31 fixed categories, at 96% confidence. This is a model’s judgement about what the channel is likely to be about, not a fact this register measured the way a subscriber count or a view count is measured — it can be revised on a later pass, and it carries no weight anywhere else on this page. How this classification works, and why it has no browse page of its own yet.
Growth
13 measurements spanning 44 days, net +88. Dots are measurements; the straight line between them is drawn to join them, not to claim we know the path taken in between — snapshots are recorded only when a count changes, so gaps mean “no change observed”, never “interpolated”. The vertical axis spans 9,512–9,629 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
19 Sept 2026, 04:01
9,615
+12
14 Sept 2026, 09:18
9,603
+7
10 Sept 2026, 22:39
9,596
+28
6 Sept 2026, 05:57
9,568
+9
29 Aug 2026, 23:33
9,559
+14
26 Aug 2026, 12:45
9,545
+11
23 Aug 2026, 20:35
9,534
-3
20 Aug 2026, 02:51
9,537
+1
16 Aug 2026, 19:37
9,536
+8
13 Aug 2026, 05:57
9,528
+3
10 Aug 2026, 05:51
9,525
-6
6 Aug 2026, 23:40
9,531
+4
6 Aug 2026, 04:15
9,527
first reading
Engagement
53 posts held, back to 30 July 2026 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 33 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
9.59%
avg views ÷ 9,615 subscribers
Avg views / post
922
9 posts measured
Reaction rate
1.84%
reactions ÷ views · ER floor
Posts in window
9
of 53 held
ERR is average views per post over the last 30 days divided by subscribers, the definition TGStat uses, so this figure is comparable with the one you will see elsewhere. It falls structurally as a channel grows: a high ERR on a small channel and a low one on a large channel describe reach mathematics, not quality. We publish the figure and the sample it came from and pass no verdict on it.
ER is defined industry-wide as (forwards + reactions + comments) ÷ views — note the denominator is views, not subscribers. Telegram’s public web preview carries views and reactions but not forward or comment counts, so the reaction rate above is the reactions term only and is therefore a floor: the true ER for this channel is higher by an amount we have not measured and will not estimate.
What these figures were computed from
Window
Rolling 30 days · latest post in window 29 August 2026
Posts held
53 (30 July 2026 – 29 August 2026)
Views total
8,295
Reactions total
153
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
29 Aug 2026, 05:54 UTC
Views are a single reading per post, taken at the time above. A post published in the last day or two is still accumulating views, which pulls the 30-day average down slightly. That is a property of the standard definition rather than a fault in it, so we keep the definition rather than “correcting” the number into something nobody can reproduce.
Precision. Telegram publishes view counts on its public widget in short form — 8.12K, 3.7M — so any reading at or above 1,000 reaches us rounded to three significant figures, and only counts below 1,000 are exact. Averages and rates derived from them are shown to the same precision rather than to the unit: a figure like 3,701,250 would assert digits nobody measured.
Reaction counts are published per emoji and rounded the same way, so a total below 1,000 is exact and a larger one is a sum that may carry a rounded component from each emoji above 1,000. Because it is a sum, it does not look rounded — read a large reaction total as three significant figures per contributing emoji rather than as the figure it prints.
What this channel posts
Video runtime
5m 18s
Average length
1m 20s
Measured directly from 4 videos with a duration reading, out of the posts we hold for this channel — not this channel’s whole posting history, only the sample this register has actually read. An exact reading to the second, taken from the post itself rather than from Telegram’s own rounded chrome, so it carries no ≈ mark.
Reaction mix
948 reactions across 51 posts, in 21 distinct kinds. The most used accounts for 46.2% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
438
46.2%
🔥
268
28.3%
👍
94
9.92%
👏
46
4.85%
🥰
33
3.48%
❤🔥
13
1.37%
😱
10
1.05%
😍
8
0.844%
🍓
6
0.633%
🤔
6
0.633%
🦄
5
0.527%
🎉
4
0.422%
💘
3
0.316%
💯
3
0.316%
custom 5312248944510671282
2
0.211%
👀
2
0.211%
😁
2
0.211%
🙏
2
0.211%
⚡
1
0.105%
👨💻
1
0.105%
1 further kind
1
0.105%
Custom emoji. One row above is a Telegram custom emoji, which the public preview renders as an element carrying only a numeric id — no character, and no image we can reach. The id is printed as-is rather than substituted with a look-alike glyph, because a stand-in would be our invention showing where a measurement should be. The count beside it is Telegram’s.
No sentiment is inferred, and none should be read in. This table is ordered by count and by nothing else. Emoji do not carry stable meaning across languages or communities — 🙏 is thanks in one channel and mourning in another — so we publish which ones were pressed and how often, and pass no judgement on what an audience meant by them.
Precision. Telegram publishes reaction counts per emoji and short-forms each one — 4.34K, 1.2M — so any single kind at or above 1,000 reaches us at three significant figures, and only counts below 1,000 are exact. The shares above are ratios of those figures and carry the same error. This is also why the total here can differ slightly from a reaction total printed elsewhere on the page: both are sums of the same rounded parts, taken over samples with different edges.
Coverage. Reactions were read on 53 of the 53 sampled posts in this sample. Summed by Telegram’s own count on each post — not by adding up the per-emoji breakdown above — those same posts carry 997 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 53 most recent posts we hold, published 30 July 2026 to 29 August 2026, using the newest reading held for each. Telegram Stars are excluded: they are a payment, not a reaction, and they have their own section.
Telegram Stars
Stars received
1
across the posts below
Posts paid on
1
of 53 we hold a reading for · 2%
Most on one post
1
single highest reading
A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @biomolecula. Telegram publishes the count on the public post preview alongside ordinary reactions, and this register reads it there. It is the only figure on this site that measures money moving rather than attention.
Stars are not reactions, and the two are never added. They are rendered in the same strip on Telegram and counted in the same shape, but one is a tap and the other is a purchase. The reaction totals and the engagement rate elsewhere on this page exclude every figure in this section, and no rate here is computed against a reaction count.
This is not revenue, and we publish no currency figure. What a Star costs a reader and what it pays a channel are different numbers, Telegram takes a share we cannot observe, and the terms have changed. Converting a Star count into money would be an estimate dressed as a measurement, so the count is where we stop.
Counted over the 53 most recent posts we hold for this entry, published 30 July 2026 to 29 August 2026. Star counts above 1,000 reach us in Telegram’s short form and carry the same three-significant-figure rounding as everything else on this page.
Advertising
Ad load
1.89%
1 of 53 posts carry an ad marker
Regulatory tokens
1
posts carrying an erid · 1 distinct token
Median views · ads
1,240
over 1 measured post
Median views · rest
1,130
over 52 measured posts
An ad marker, not a judgement about a post. A post is counted here because it carries one of two explicit markings: an erid token, which Russian law has required on paid placements since 2022 and which is issued against a specific advertising contract, or a #реклама / #ad hashtag in the body, which is the channel declaring it itself. The first is documentary; the second is a self-declaration and is weaker. No classifier reads the text and decides — nothing on this site guesses that a post is an advertisement.
This is a floor, and it can only ever be a floor. A channel that runs paid placements without marking them produces no marker for us to count, and an unmarked ad is indistinguishable from an ordinary post on the public surface. The ad load above therefore means “the share of posts that declared themselves”, never “the share of posts that were paid for”. A low figure is not evidence of a channel that runs few ads.
Both figures are medians, and no ratio between them is published. Each is a view reading that actually occurred on a post, picked by percentile_disc rather than averaged, so one viral post cannot move it and no interpolated value is invented between two readings. The sample on one side is under five posts, which is too thin to compare. The two figures are shown side by side with the count behind each, and deliberately not divided into a headline like “ads get x% fewer views” — an arithmetic that is easy to print and, at this sample size, means nothing.
Advertising tokens recorded on this entry
erid
Posts
First seen
Last seen
2Vfnxw4LyJb
1
10 August 2026
10 August 2026
A token repeated across several posts is one advertising contract placed more than once, which is what the identifier is for. The strings are reproduced exactly as they appeared in the post or in its click-through URL and are not validated against any registry — we record the marker a channel published, and whether it resolves to a real contract is a question for the register that issued it.
Measured over the 53 most recent posts we hold, published 30 July 2026 to 29 August 2026. Views are the latest single reading held for each post, and any reading at or above 1,000 is rounded by Telegram to three significant figures.
В серии «МИРЫ» издательства «Альпина.Дети» пополнение — книга о жизни и труде русского ботаника, селекционера и генетика Николая Ивановича Вавилова. Ученого, на идеях которого спустя почти 100 лет после его смерти построена работа современных растениеводов со всего мира. А еще — удивительно смелого и бескорыстного человека, отважного путешественника и прекрасного организатора.
Оценка «Биомолекулы»: 9/10
Кому подойд…
Предсказание пространственной структуры белка — задача, сформулированная еще Кристианом Анфинсеном, — на протяжении десятилетий решалась лишь косвенно. Ситуация радикально изменилась с появлением AlphaFold 1/2. Его успех был настолько значительным, что уже ознаменовался Нобелевской премией (в 2024 г.) и породил ощущение, что проблема в целом «закрыта».
Однако история этим не закончилась: современная версия — AlphaFo…
🏆 Открыт приём заявок в Акселератор МГУ 2026!
Акселератор МГУ – образовательная программа по предпринимательству и развитию стартапов для студентов, аспирантов, сотрудников, выпускников МГУ и других вузов при поддержке химического и экономического факультетов Московского университета, Научного парка МГУ и Бизнес-инкубатора МГУ.
К участию приглашаются команды на разных стадиях развития — от идеи до TRL 5+, а также …
«Что-то с сосудами» — часто говорят о мигрени, но это совсем не так! В центре приступа мигрени находится тригеминоваскулярная (повторите быстро три раза) система — тройничный нерв и его волокна, окружающие сосуды мозга и твердую мозговую оболочку.
Когда эти волокна активируются, они выбрасывают сигнальные молекулы, прежде всего CGRP. Он усиливает воспалительный ответ и повышает чувствительность болевых рецепторов. П…
Книга «Научное волонтерство. Делаем науку вместе» Александры Борисовой-Сале и Яны Плехович посвящена теме, которая еще десять-пятнадцать лет назад казалась экзотической даже для научного сообщества. Представление о том, что непрофессионалы могут участвовать в настоящих исследованиях, долгое время воспринималось как нечто второстепенное по отношению к «большой» академической науке. Однако развитие цифровых технологий,…
Давайте разбираться, как ботулотоксину удается действовать так удивительно точечно!
Ботулотоксин типа А — BoNT/A — состоит из двух функциональных частей. Тяжелая цепь помогает токсину найти активный нейрон и попасть внутрь клетки, а легкая — цинк-зависимая протеаза — делает всю работу дальше.
Сначала токсин связывается с рецепторами на поверхности активного нейрона и захватывается клеткой. Внутри эндосомы изменение…
Статья на конкурс «Био/Мол/Текст»
Морской десант: ДНК-анализ помогает проследить «тайные тропы» волжских рыб-вселенцев
Почти половина массовых видов рыб в некоторых водохранилищах Волги — чужеродные. Откуда они приплыли, почему морфология не всегда справляется с их идентификацией и при чем тут древнее море Паратетис?
Читайте на нашем сайте.
Авторы: Дмитрий Карабанов, Алексей Котов
#Биомолтекст2026_27
📰 Выбор научного сообщества: впервые OpenBio запускает конкурс российских разработок
Российские лаборатории ищут замену зарубежным реагентам, приборам и IT-системам — и не всегда знают, что нужное решение уже существует. Мы хотим это исправить.
OpenBio запускает конкурс «Выбор научного сообщества» — для компаний, стартапов и научных институтов, которые самостоятельно разрабатывают и производят продукты для исследо…
Трансмиссивный рак, при котором между особями передаются сами злокачественные клетки, — явление чрезвычайно редкое. До недавнего момента было известно три разновидности таких опухолей — трансмиссивная венерическая опухоль собак, лицевые опухоли тасманийского дьявола и заразные лейкемии у некоторых видов двустворчатых моллюсков. Однако недавно ученые открыли еще одну форму заразного рака — меланому американских сомико…
У почти каждого из нас хотя бы раз в жизни болела голова. Но представьте, что она болит 15 и более дней в месяц. А людям с хронической мигренью и представлять не надо! Хроническая мигрень — это тяжелая форма заболевания, которая серьезно влияет на повседневную жизнь и при которой помогают мало какие препараты.
Среди множества лекарств для лечения и профилактики головной боли ботулинический токсин стоит особняком. Он…
Из нового дайджеста вы узнаете о нейронных механизмах сна, мозговых органоидах, противовирусных стратегиях бактерий, причинах нарушения свертывания крови при хронической болезни почек и использовании фрагментов внеклеточной ДНК для прогнозирования неблагоприятных исходов беременности.
Читайте на нашем сайте.
Приятного чтения!
Автор: Алексей Королёв
#Биомолекула_дайджест
Несмотря на то, что книга с громоздким названием «Рационально-эмотивная поведенческая терапия. Полный курс от Альберта Эллиса» не обещает увлекательного чтения, внутри нее прячется много интересного и полезного о нашей психике.
Оценка «Биомолекулы»: 8,3/10
Кому подойдет: психотерапевтам, обучающимся и практикующим, а также людям, которые интересуются методами по изменению собственного мышления.
Читайте на сайте.
…
❤10
Showing the 12 most recent of 53 posts we hold for @biomolecula. View and reaction counts are the latest single reading for each post, not a live figure, and a recent post is still accumulating both. A view count marked ≈ was rounded by Telegram before we ever saw it — t.me prints views in full below 1,000 and to three significant figures above, so ≈1,200,000 means somewhere between 1,150,000 and 1,249,999. Unmarked counts are exact. Text is reproduced from the public post preview and truncated for length.
Forward network
Republished by
Channels on the register that have forwarded this channel's posts into their own feed.
Built only from forwarded posts we have actually read, on both sides. Coverage is early and deliberately incomplete: a missing link means we have not read the post that would prove it, never that the relationship does not exist. Counts are distinct forwarded posts observed, so they only ever go up as we read more.
Mentions
Named by 7 registered channels — every channel on the register whose own posts have named this one, by its current username or any other username it currently holds, merged from two separately captured readings of the same fact so a namer caught by only one of them is not missed and a namer both caught is not counted twice. A username this channel has since dropped is not matched — that handle may belong to someone else now, and crediting today’s namer to yesterday’s owner would misattribute it.
Named by
Channels on the register whose posts name this channel's handle.
A mention is a weaker signal than a forward and is counted separately for that reason — naming a channel is not republishing it, and a handle in a post body is easy to place deliberately. The post counts beside each row below are distinct posts in which the handle appeared, from posts we have read on both sides — the “Named by N registered channels” figure above is a different count, of distinct NAMING CHANNELS rather than posts, and is not the sum of the rows under it.
Appears in Telegram’s recommendations for other channels
The reverse of the list above, and a different kind of signal. This does not require this channel to have ever been asked about directly — each row below is a channel we DID ask Telegram about, whose Telegram-generated list happened to include this one. A channel can appear here with an empty list above it, because being named by someone else’s query is independent of having been queried itself.
Sci_Career @sci_career · 30,335 Telegram ranks this channel #13 of 92 here — alongside 91 others — read 7 September 2026
Медач | Medical Channel @medach · 28,118 Telegram ranks this channel #24 of 97 here — alongside 96 others — read 10 September 2026
Зоопарк из слоновой кости @ivoryzoo · 31,450 Telegram ranks this channel #55 of 97 here — alongside 96 others — read 6 September 2026
This channel appears in 3 seed channels' Telegram-generated recommendation lists in total. Each is Telegram’s list for THAT channel, not this one — see how this is measured.
Cite this entry
A live page changes as we take new readings, so a citation should name the measurement it is based on, not just the URL. The line below cites the subscriber count as measured 19 September 2026 — this
entry's latest reading, not the date you are reading this.
“Биомолекула” (@biomolecula), 9,615 subscribers as measured 19 September 2026. Telegram Register, tgregister.com/channel/biomolecula.
Full measurement history, CC BY 4.0. Every reading this register holds for this entry, not just the latest one, as a dated, downloadable record: CSV · JSON. Free to use with attribution to tgregister.com. Each file carries its own generation timestamp, which is the figure to cite for exactly when the data was retrieved.