Multi-OMICS and Molecular Biology Perspective in Buffalo Genome
Bibliographic record
Abstract
The bovine species buffalo was domesticated from its wild strain Bubalus arnee and is widely used livestock in southern Asia. There are two distinct types of Buffalo- the swamp buffalo (B. bubalis kerebau) and the river buffalo (B. bubalis bubalis), which diverged from the wild Asian water buffalo and then evolved in separate geographical regions. Several research studies performed on buffalo, like- characterization of trait-specific Single Nucleotide Polymorphism (SNP), genetic and phenotypic diversity, gene prediction and function annotation, mapping of the draft genome, have helped our understanding of the buffalo genome. Some advanced discovery as identification of Single Nucleotide Variant (SNVs), Simple Sequence Repeats (SSR) marker and their association with various phenotypic traits, MicroRNA's expression profiling, whole-genome sequencing, etc. have also enabled us to track the chromosomal evolution, physiological processes, and gene expression of buffalo. Proper enhancement of these traits can lead us to apply multi-omics-based tools for better animal health and production. Recent advancement in genomic research on buffalo is being accelerated with the association of modern tools like- Genome-Wide Association Study (GWAS), genotyping by sequencing, epigenomic screening, microRNA's expression profiling, microarray technology, and whole-genome sequencing. All these tools bear great significance in breed up-gradation, identification of the phylogenetic relationship between species in proteome and genomic level, study gene expression level, diagnose diseases or developmental stages, phenotypic diversity, etc. All this knowledge paved the way for better optimization of production efficiency, product quality, and resistance to certain health hazards.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".