[ExI] 1 mm^3 of brain

Tue May 28 02:47:36 UTC 2024

A different take from another AI (GPT-4o):
is the human genome inherently compressed data

The human genome can be thought of as inherently compressed in a biological
sense because it uses a highly efficient system to store genetic
information. Here are a few key points to understand this concept:

   1.

   DNA Structure: The human genome consists of DNA, which is composed of
   four nucleotides (adenine, thymine, cytosine, and guanine). The sequence of
   these nucleotides encodes the genetic information.
   2.

   Coding vs. Non-coding Regions: Only a small portion of the genome (about
   1-2%) actually codes for proteins. The rest consists of non-coding regions,
   some of which have regulatory functions, while others are less understood
   or considered "junk" DNA. This means that a large portion of the genome
   does not directly contribute to the coding of proteins, suggesting an
   efficient way to store information where not all sequences are equally
   critical.
   3.

   Genetic Redundancy and Repetitive Elements: The human genome contains
   many repetitive elements and sequences. Some sequences are repeated
   multiple times throughout the genome, and there are mechanisms to use these
   repetitions efficiently, akin to data compression in computational terms.
   4.

   Chromatin Structure: DNA is wrapped around histone proteins to form
   nucleosomes, which further coil and fold into higher-order structures. This
   packaging not only helps to fit the large amount of DNA into the nucleus
   but also regulates gene expression and access to genetic information.
   5.

   Epigenetic Regulation: Beyond the nucleotide sequence, epigenetic
   modifications (such as DNA methylation and histone modification) provide
   additional layers of information and regulation without altering the
   underlying DNA sequence. This can be viewed as another form of data
   compression, where additional information is overlaid on the genetic code.

While these biological mechanisms are not compression in the digital sense,
they represent ways the genome efficiently stores and regulates vast
amounts of information.

On Mon, May 20, 2024 at 12:20 PM BillK via extropy-chat <
extropy-chat at lists.extropy.org> wrote:

> On Mon, 20 May 2024 at 15:26, Will Steinberg via extropy-chat <
> extropy-chat at lists.extropy.org> wrote:
> >
> > @john: the human genome IS compressed data.
> > _______________________________________________
>
>
> Hi Will
>
> Genetic researchers can compress the human genome.
> BillK
>
> I asked -
> Is the human genome already compressed data, or can it be stored in a
> compressed format?
>
> Perplexity Pro AI -
>
> The human genome is not inherently compressed data, but it can be stored
> in a compressed format. The vast amount of genomic data generated by modern
> sequencing technologies necessitates efficient storage solutions, and
> various specialized compression algorithms have been developed to address
> this need.
>
> ### Compression Methods for Genomic Data
>
> 1. **SparkGC**:
>    - SparkGC is an Apache Spark-based genome compression method designed
> to handle large collections of genomes efficiently. It uses Resilient
> Distributed Datasets (RDD) transformations to keep data active in memory
> throughout the compression process, significantly improving compression
> speed and scalability. SparkGC can compress 1100 human genomes on a common
> computer with just 24 GB of RAM, achieving the best compression ratio among
> state-of-the-art methods[1].
>
> 2. **Lossless DNA Compression Algorithm**:
>    - This method specializes in compressing nucleotide sequence data in
> FASTA/multi-FASTA formats. It separates the headers and uses 7-Zip for
> compression, achieving a high compression ratio by leveraging the specific
> characteristics of DNA sequences[2].
>
> 3. **LZ77 and CTW Algorithms**:
>    - A method combining the LZ77 algorithm with the context tree weighting
> (CTW) algorithm has been proposed to compress DNA data. This approach first
> converts DNA sequences into intermediate files before applying LZ77,
> resulting in significant reductions in compression and decompression times
> while maintaining a high compression rate[3].
>
> 4. **Neural Network-Based Compression (GeCo3)**:
>    - GeCo3 uses a neural network metamodel to improve the compression
> ratio of DNA sequences. It benchmarks both reference-free and referential
> compression, showing consistent improvements over other state-of-the-art
> DNA compressors. This method is particularly useful for long-term storage
> and sequence analysis[4].
>
> 5. **FQSqueezer**:
>    - FQSqueezer is a novel algorithm for compressing sequencing data,
> particularly FASTQ files. It uses prediction by partial matching (PPM) and
> dynamic Markov coder (DMC) algorithms, achieving better compression ratios
> than existing tools. However, it requires significant memory and time
> resources[5].
>
> ### Conclusion
>
> The human genome can indeed be stored in a compressed format using
> specialized algorithms designed to handle the unique characteristics of
> genomic data. These methods significantly reduce the storage requirements
> and improve the efficiency of data handling in genomic research and
> applications.
>
> Citations:
> [1]
> https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-022-04825-5
> [2] https://www.mdpi.com/1999-4893/13/4/99
> [3] https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7688149/
> [4] https://academic.oup.com/gigascience/article/9/11/giaa119/5974977
> [5] https://www.nature.com/articles/s41598-020-57452-6
> [6]
> https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-023-05500-z
> [7] https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9337911/
> [8] https://www.reddit.com/r/askscience/comments/637gyu/is_dna_compressed/
> [9] https://arxiv.org/abs/2006.02232
> [10] https://www.sciencedirect.com/science/article/pii/S2666389922001738
> [11]
> https://www.frontiersin.org/journals/genetics/articles/10.3389/fgene.2023.1260531/full
> [12] https://en.wikipedia.org/wiki/Compression_of_genomic_sequencing_data
> [13] https://github.com/rajatdiptabiswas/dna-compression
> [14] https://arxiv.org/abs/2401.14025
> [15] https://www.sciencedirect.com/science/article/pii/S1877050916318762
> [16]
> https://www.illumina.com/documents/products/whitepapers/whitepaper_datacompression.pdf
> [17] https://arxiv.org/abs/2311.01431
> [18]
> https://blog.chiariglione.org/genome-is-digital-and-can-be-compressed/
> [19] https://pubmed.ncbi.nlm.nih.gov/37018338/
> [20]
> https://genomebiology.biomedcentral.com/articles/10.1186/s13059-021-02443-7
> ------------------------------------
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