4 ms·

Okay, „parts“ for me was just a word to refer to the machine, it is also okay if it is only a single part. It still remains a machine in the sense that it perfo

by quonn 2y ago

Okay, „parts“ for me was just a word to refer to the machine, it is also okay if it is only a single part. It still remains a machine in the sense that it performs a task it should perform and does so using the same approach across all instances. That the „parts“ do not only perform a specific function is not really surprising, because the machine does not need to be comprehensible or understandable. I would expect single-purpose parts only if that helps the function or if it helps evolvability (in the sense of not creating dead ends).

roywiggins 2y ago
The paper covers this also. Cells don't behave predictably: > The variable flickering of transcriptional activity in different cells is one of the major causes of heterogeneity in isogenic populations. But where exactly does this cell-to-cell variability in transcriptional activity come from? The answer becomes apparent when we remember that gene expression is a molecular process, and like all molecular processes, it is inherently stochastic, given that it takes place in an environment that is subject to the chaotic dynamics of Brownian motion. Each step in the process relies on fortuitous encounters between molecules that are randomly moving about as a consequence of thermal agitation. Evidently, these molecules must be at the right place and at the right time—not to mention in the right vibrational state—for them to be able to participate in the appropriate reactions. The unpredictability of the whole process is further amplified by the fact that the participating molecules in each step are present in the cell in very low copy-numbers, as this decreases the chances of successful interactions between them... > as research into the non-genetic heterogeneity of cells continues, evidence for the biological importance of this phenomenon is mounting ever-rapidly. We now know that non-genetic heterogeneity plays key roles in both microbial and eukaryotic cells, in embryonic development, and in evolution. For one thing, it is a crucial generator of phenotypic diversity, which enables cell populations to adapt rapidly to changing environmental conditions. It does so by permitting the implementation of probabilistic diversification strategies within a population, such as bet-hedging and divisions of labour, which can confer considerable fitness advantages... > One very important theoretical implication of the probabilistic nature of cellular behaviour and the observed heterogeneity of cell populations is that, quite literally, every cell (in an organism and elsewhere) is a unique entity. No two cells are identical, given that no two cells respond to a stimulus in the exact same way—even if they are genetically the same.
- generalizations 2y ago
  It's just a very, very optimized & elegant design. Reminds me of this: He had located the data he was working on near the top of memory --- the largest locations the instructions could address --- so, after the last datum was handled, incrementing the instruction address would make it overflow. The carry would add one to the operation code, changing it to the next one in the instruction set: a jump instruction. Sure enough, the next program instruction was in address location zero, and the program went happily on its way. And it's not like our own transistors aren't probabalistic when you look closely enough.
  - JoeAltmaier 2y ago
    Anecdote: had an 8086 system-call jump table that fielded up to 64K calls, but using a jump table of 4K. Address mode was segment:offset where segment was 17 bits and offset 16, but shifted by 4. The table consisted of the same trap instruction throughout, which took 4 bytes. If I remember it all right. Anyway the system call trap examined the caller stack, found the return address (to the trap table), picked out the combination of segment and offset used to construct a system-call index. Following so far? We went paged. Changed syscall segment to indirect, 16 segment descriptors all mapped to the start of the jump table. Started failing on one particular system call out of thousands - it would page fault! Why? The auto-increment and prefetch of the trap opcode in the jump table would fault, for only one syscall, the one that mapped to the last entry in the trap table where the offset came out to 0FFC. Wrapped to 1000, which with that particular segment meant next-page! Which was unmapped (system trap table was in low memory, alone). My solution: change the syscall index for that operation to something else, and document in the syscall comments to never use it.
  - roywiggins 2y ago
    If a computer running a probabilistic calculation got it right 90% of the time, and the next one over running the same calculation on identical hardware got it right 10% of the time, there would be something wrong with the computer. This is not true with cells.

by quonn 2y ago

roywiggins 2y ago

The paper covers this also. Cells don't behave predictably: > The variable flickering of transcriptional activity in different cells is one of the major causes of heterogeneity in isogenic populations. But where exactly does this cell-to-cell variability in transcriptional activity come from? The answer becomes apparent when we remember that gene expression is a molecular process, and like all molecular processes, it is inherently stochastic, given that it takes place in an environment that is subject to the chaotic dynamics of Brownian motion. Each step in the process relies on fortuitous encounters between molecules that are randomly moving about as a consequence of thermal agitation. Evidently, these molecules must be at the right place and at the right time—not to mention in the right vibrational state—for them to be able to participate in the appropriate reactions. The unpredictability of the whole process is further amplified by the fact that the participating molecules in each step are present in the cell in very low copy-numbers, as this decreases the chances of successful interactions between them... > as research into the non-genetic heterogeneity of cells continues, evidence for the biological importance of this phenomenon is mounting ever-rapidly. We now know that non-genetic heterogeneity plays key roles in both microbial and eukaryotic cells, in embryonic development, and in evolution. For one thing, it is a crucial generator of phenotypic diversity, which enables cell populations to adapt rapidly to changing environmental conditions. It does so by permitting the implementation of probabilistic diversification strategies within a population, such as bet-hedging and divisions of labour, which can confer considerable fitness advantages... > One very important theoretical implication of the probabilistic nature of cellular behaviour and the observed heterogeneity of cell populations is that, quite literally, every cell (in an organism and elsewhere) is a unique entity. No two cells are identical, given that no two cells respond to a stimulus in the exact same way—even if they are genetically the same.

generalizations 2y ago
It's just a very, very optimized & elegant design. Reminds me of this: He had located the data he was working on near the top of memory --- the largest locations the instructions could address --- so, after the last datum was handled, incrementing the instruction address would make it overflow. The carry would add one to the operation code, changing it to the next one in the instruction set: a jump instruction. Sure enough, the next program instruction was in address location zero, and the program went happily on its way. And it's not like our own transistors aren't probabalistic when you look closely enough.
- JoeAltmaier 2y ago
  Anecdote: had an 8086 system-call jump table that fielded up to 64K calls, but using a jump table of 4K. Address mode was segment:offset where segment was 17 bits and offset 16, but shifted by 4. The table consisted of the same trap instruction throughout, which took 4 bytes. If I remember it all right. Anyway the system call trap examined the caller stack, found the return address (to the trap table), picked out the combination of segment and offset used to construct a system-call index. Following so far? We went paged. Changed syscall segment to indirect, 16 segment descriptors all mapped to the start of the jump table. Started failing on one particular system call out of thousands - it would page fault! Why? The auto-increment and prefetch of the trap opcode in the jump table would fault, for only one syscall, the one that mapped to the last entry in the trap table where the offset came out to 0FFC. Wrapped to 1000, which with that particular segment meant next-page! Which was unmapped (system trap table was in low memory, alone). My solution: change the syscall index for that operation to something else, and document in the syscall comments to never use it.
- roywiggins 2y ago
  If a computer running a probabilistic calculation got it right 90% of the time, and the next one over running the same calculation on identical hardware got it right 10% of the time, there would be something wrong with the computer. This is not true with cells.