diff --git a/docs/challenges/knapsack.md b/docs/challenges/knapsack.md index e1901087..4ad742d1 100644 --- a/docs/challenges/knapsack.md +++ b/docs/challenges/knapsack.md @@ -47,7 +47,7 @@ The Knapsack problems have a wide variety of practical applications. The [use of Although originally studied in the context of logistics, Knapsack problems appear regularly in diverse areas of science and technology. For example, in gene expression data, there are usually thousands of genes, but only a subset of them are informative for a specific problem. The Knapsack Problem can be used to select a subset of genes (items) that maximises the total information (value) without exceeding the limit of the number of genes that can be included in the analysis (weight limit). -Gene Clustering +Gene Clustering
Figure 2: Microarray clustering of differentially expressed genes in blood. Genes are clustered in rows, with red indicating high expression, yellow intermediate expression and blue low expression. The Knapsack problem is used to analyse gene expression clustering.
diff --git a/docs/challenges/satisfiability.md b/docs/challenges/satisfiability.md index d3acaa57..581dabfc 100644 --- a/docs/challenges/satisfiability.md +++ b/docs/challenges/satisfiability.md @@ -65,7 +65,7 @@ SAT has a vast range of applications in science and industry in fields including SAT is used in computational biology to solve the "cell formation problem" of [organising a plant into cells](https://www.sciencedirect.com/science/article/abs/pii/S0957417412006173). SAT is also heavily utilised in [electronic circuit design](https://dl.acm.org/doi/abs/10.1145/337292.337611). -Application of SAT +Application of SAT
Figure 1: Chips made possible by electronic circuit design.

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